Deep Learning



Best matching news and articles for Deep Learning


Title Summary/Keywords
Banach Space Representer Theorems for Neural Networks and Ridge Splines
http://jmlr.org/ | Today
Content: We develop variational framework to understand the properties of the functions learned by neural networks fit to data. We propose and study family of continuous domain linear inverse problems with total variation like regularization in the Radon domain subject to data fitting constraints. We derive representer theorem showing that finite width, single hidden layer neural networks are solutions to these inverse problems. We draw on many techniques from variational spline theory and so we pr...

Keywords: design, framework, network, neural network
Support Vector Machines vs Multiplicative Neuron Model Neural Network in Prediction of Bank Failures
http://article.sapub.org/ | Yesterday
Content: Publication year 2017Source American Journal of Intelligent Systems, Volume 7, Number 5Birsen Eygi Erdoan, Erol Eriolu, Esra AkdenizSupport Vector Machines have been developed as an alternative for classification problems to the classical learning algorithms, such as Artificial Neural Network. Thanks to advantages of using kernel trick, having global optimum and simple geometric interpretation support vector machines are known as the best classifiers among others. Classical learning...

Keywords: metric, ios, algorithms, neural network
Phase Diagram for Two-layer ReLU Neural Networks at Infinite-width Limit
http://jmlr.org/ | Today
Content: How neural network behaves during the training over different choices of hyperparameters is an important question in the study of neural networks. In this work, inspired by the phase diagram in statistical mechanics, we draw the phase diagram for the two layer ReLU neural network at the infinite width limit for complete characterization of its dynamical regimes and their dependence on hyperparameters related to initialization. Through both experimental and theoretical approaches, we identify...

Keywords: network, neural network, statistic
Why Choose Deep Learning
https://www.youtube.com/ | Yesterday
Content: This video introduces deep learning from the perspective of solving practical engineering problems. Learn why deep learning may be the method of choice.Get free product trial Learn more about MATLAB Learn more about Simulink See what s new in MATLAB and Simulink 2021 The MathWorks, Inc. MATLAB and Simulink are registered trademarks of The MathWorks, Inc. See for list of additional trademarks. Other product or brand names may be trademarks or registered trademarks of their respective...

Keywords: deep learning, matlab
Neural Networks as Geometric Chaotic Maps
https://arxiv.org | Yesterday
Content: The use of artificial neural networks as models of chaotic dynamics has been rapidly expanding, but the theoretical understanding of how neural networks learn chaos remains lacking. Here, we employ a geometric perspective to show that neural networks can efficaciously model chaotic dynamics by themselves becoming structurally chaotic. First, we confirm the efficacy of neural networks in emulating chaos by showing that parsimonious neural networks trained only on few data points suffice to recons...

Keywords: metric, network, neural network
A State-of-the-art Survey of Artificial Neural Networks for Whole-slide Image Analysis:from Popular Convo...
https://arxiv.org | Yesterday
Content: In recent years, with the advancement of computer-aided diagnosis (CAD) technology and whole slide image (WSI), histopathological WSI has gradually played a crucial aspect in the diagnosis and analysis of diseases. To increase the objectivity and accuracy of pathologists' work, artificial neural network (ANN) methods have been generally needed in the segmentation, classification, and detection of histopathological WSI. In this paper, WSI analysis methods based on ANN are reviewed. Firstly, the d...

Keywords: metric, r , neural network
Anomaly Detection in Image Datasets Using Convolutional Neural Networks, Center Loss, and Mahalanobis Distance
https://arxiv.org | Yesterday
Content: User activities generate a significant number of poor-quality or irrelevant images and data vectors that cannot be processed in the main data processing pipeline or included in the training dataset. Such samples can be found with manual analysis by an expert or with anomalous detection algorithms. There are several formal definitions for the anomaly samples. For neural networks, the anomalous is usually defined as out-of-distribution samples. This work proposes methods for supervised and semi-su...

Keywords: neural network, network, analysis, classification
Bayesian Optimisation for a Biologically Inspired Population Neural Network
https://arxiv.org | Yesterday
Content: We have used Bayesian Optimisation (BO) to find hyper-parameters in an existing biologically plausible population neural network. The 8-dimensional optimal hyper-parameter combination should be such that the network dynamics simulate the resting state alpha rhythm (8 - 13 Hz rhythms in brain signals). Each combination of these eight hyper-parameters constitutes a 'datapoint' in the parameter space. The best combination of these parameters leads to the neural network's output power spectral peak ...

Keywords: tpu, network, neural network
Self-supervised Auxiliary Learning for Graph Neural Networks via Meta-Learning
https://arxiv.org | Yesterday
Content: In recent years, graph neural networks (GNNs) have been widely adopted in the representation learning of graph-structured data and provided state-of-the-art performance in various applications such as link prediction, node classification, and recommendation. Motivated by recent advances of self-supervision for representation learning in natural language processing and computer vision, self-supervised learning has been recently studied to leverage unlabeled graph-structured data. However, employi...

Keywords: neural network, natural language processing
A Deep Learning Architecture for Conservative Dynamical Systems: Application to Rainfall-Runoff Modeling
https://research.google/ | Yesterday
Content: The most accurate and generalizable rainfall runoff models produced by the hydrological sciences community to date are based on deep learning, and in particular, on Long Short Term Memory networks LSTMs . Although LSTMs have an explicit state space and gates that mimic input state output relationships, these models are not based on physical principles. We propose deep learning architecture......

Keywords: tpu, deep learning, network
Computer Scientists From Rice University Display CPU Algorithm That Trains Deep Neural Networks 15 Times ...
https://www.marktechpost.com/ | Yesterday
Content: Computer scientists from Rice University have displayed an artificial intelligence AI software that can run on commodity processors and train deep neural networks 15 times faster than platforms based on graphics processors. According to Anshumali Shrivastava, an assistant professor of computer science at Rice 8217 s Brown School of Engineering, the resources spent on training are the 8230 The post Computer Scientists From Rice University Display CPU Algorithm That Trains Deep Neural Netwo...

Keywords: cpu, network, ai , neural
Large Data Analysis via Interpolation of Functions: Interpolating Polynomials vs Artificial Neural Networks
http://article.sapub.org/ | Yesterday
Content: Publication year 2018Source American Journal of Intelligent Systems, Volume 8, Number 1Rohit RaturiIn this article we study function interpolation problem from interpolating polynomials and artificial neural networks point of view. Function interpolation plays very important role in many areas of experimental and theoretical sciences. Usual means of function interpolation are interpolation polynomials Lagrange, Newton, splines, Bezier, etc. . Here we show that specific strategy of functi...

Keywords: network, data analysis, analysis, neural
Global Convergence of Second-order Dynamics in Two-layer Neural Networks
https://research.google/ | Yesterday
Content: Recent results have shown that for two layer fully connected neural networks, gradient flow converges to global optimum in the infinite width limit, by making connection between the mean field dynamics and the Wasserstein gradient flow. These results were derived for first order gradient flow, and natural question is whether second order dynamics, i.e., dynamics with momentum, exhibit a......

Keywords: neural network, network
Fusion of convolution neural network, support vector machine and Sobel filter for accurate detection of C...
https://www.docwirenews.com/ | Yesterday
Content: Fusion of convolution neural network, support vector machine and Sobel filter for accurate detection of COVID 19 patients using X ray imagesDocWire News...

Keywords: neural network, network
Knowing More about Neural Networks
https://networking.cioreview.com/ | Today
Content: 4317 This radial network visualization depicts the connections among common science fiction tropes and plot elements, and the famous movies which might or might not feature these themes. 3462 The sheer volume of people migrating to Austin from all over the country, but particularly from the San Francisco Bay Area, has been making headlines for while now.One result of this continued migration is steady surge in housing prices due to increased demand and low inventory that dropped to nearly zero earlier this year. Now, Homebound, Santa Rosa, California based tech enabled homebuilding startup, is entering the Austin market with the goal of helping ease some of the pain felt in the city by offering an alternative to buying existing homes.Homebound has raised about 73 million over the years from the likes of Google Ventures, Fifth Wall, Khosla, Sound Ventures, Atomic and Thrive Capital. It raised 35 million Series last April and then closed on 20 million convertible note late last year. ...

Keywords: design, test, turing, visual, network
Researchers At The University Of Houston Propose A New Artificial Neural Network Design That Can Differen...
https://www.marktechpost.com/ | Yesterday
Content: The Biomedical Engineering Department 8217 s founding chair at the University of Houston has reported new deep neural network architecture capable of providing early diagnosis of systemic sclerosis SSc . It is rare auto immune disease characterized by hardened or fibrous skin and internal organs. The proposed network can be implemented using standard laptop computer with 8230 The post Researchers At The University Of Houston Propose New Artificial Neural Network Design That Can Dif...

Keywords: ai , test, mobile, classification
404.zero utilise neural networks and analog synthesisers in Deep Echo - FACT
https://www.factmag.com/ | Today
Content: 404.zero utilise neural networks and analog synthesisers in Deep EchoFACT...

Keywords: network, neural network
The Convex Relaxation Barrier, Revisited: Tightened Single-Neuron Relaxations for Neural Network Verification
https://research.google/ | Yesterday
Content: We improve the effectiveness of propagation and linear optimization based neural network verification algorithms with new tightened convex relaxation for ReLU neurons. Unlike previous single neuron relaxations which focus only on the univariate input space of the ReLU, our method considers the multivariate input space of the affine pre activation function preceding the ReLU. Using results......

Keywords: neural network, network, algorithms
Machine Learning and AI Neural Networks at Work in Blue Ridge Price Optimization - Press Release - Digita...
http://www.digitaljournal.com/ | Yesterday
Content: Machine Learning and AI Neural Networks at Work in Blue Ridge Price Optimization Press ReleaseDigital Journal...

Keywords: neural network, network, machine learning
MicroNets: Neural Network Architectures for Deploying TinyML Applications on Commodity Microcontrollers
https://arxiv.org | Yesterday
Content: Executing machine learning workloads locally on resource constrained microcontrollers (MCUs) promises to drastically expand the application space of IoT. However, so-called TinyML presents severe technical challenges, as deep neural network inference demands a large compute and memory budget. To address this challenge, neural architecture search (NAS) promises to help design accurate ML models that meet the tight MCU memory, latency and energy constraints. A key component of NAS algorithms is th...

Keywords: machine learning, design, neural network
Explaining Neural Network Predictions on Sentence Pairs via Learning Word-Group Masks
https://arxiv.org | Yesterday
Content: Explaining neural network models is important for increasing their trustworthiness in real-world applications. Most existing methods generate post-hoc explanations for neural network models by identifying individual feature attributions or detecting interactions between adjacent features. However, for models with text pairs as inputs (e.g., paraphrase identification), existing methods are not sufficient to capture feature interactions between two texts and their simple extension of computing all...

Keywords: bert , neural network, computing
Self-adaptive loss balanced Physics-informed neural networks for the incompressible Navier-Stokes equations
https://arxiv.org | Yesterday
Content: There have been several efforts to Physics-informed neural networks (PINNs) in the solution of the incompressible Navier-Stokes fluid. The loss function in PINNs is a weighted sum of multiple terms, including the mismatch in the observed velocity and pressure data, the boundary and initial constraints, as well as the residuals of the Navier-Stokes equations. In this paper, we observe that the weighted combination of competitive multiple loss functions plays a significant role in training PINNs e...

Keywords: network, neural network
Complex-Valued vs. Real-Valued Neural Networks for Classification Perspectives: An Example on Non-Circula...
https://arxiv.org | Yesterday
Content: The contributions of this paper are twofold. First, we show the potential interest of Complex-Valued Neural Network (CVNN) on classification tasks for complex-valued datasets. To highlight this assertion, we investigate an example of complex-valued data in which the real and imaginary parts are statistically dependent through the property of non-circularity. In this context, the performance of fully connected feed-forward CVNNs is compared against a real-valued equivalent model. The results show...

Keywords: python library, neural network, python
Vertically Federated Graph Neural Network for Privacy-Preserving Node Classification
https://arxiv.org | Yesterday
Content: Recently, Graph Neural Network (GNN) has achieved remarkable progresses in various real-world tasks on graph data, consisting of node features and the adjacent information between different nodes. High-performance GNN models always depend on both rich features and complete edge information in graph. However, such information could possibly be isolated by different data holders in practice, which is the so-called data isolation problem. To solve this problem, in this paper, we propose VFGNN, a fe...

Keywords: r , neural network, network
Deep Learning model developed at UHN to maximize lifespan after liver transplant - EurekAlert
https://www.eurekalert.org/ | Yesterday
Content: Deep Learning model developed at UHN to maximize lifespan after liver transplantEurekAlert...

Keywords: deep learning
Autoencoder Anomaly Detection Using PyTorch
https://www.google.com/ | Yesterday
Content: To run the demo program, you must have Python and PyTorch installed on your machine. The demo programs were developed on Windows 10 using......

Keywords: python, pytorch
Balance Regularized Neural Network Models for Causal Effect Estimation
https://research.google/ | Yesterday
Content: Estimating individual and average treatment effects from observational data is an important problem in many domains such as healthcare and e commerce. In this paper, we advocate balance regularization of multi head neural network architectures. Our work is motivated by representation learning techniques to reduce differences between treated and untreated distributions that potentially arise due......

Keywords: neural network, network
Proposed Neural Network with FFT Transfer Function to Estimate Henon Dynamical Map
http://article.sapub.org/ | Yesterday
Content: Publication year 2019Source American Journal of Intelligent Systems, Volume 9, Number 1Salah H. Abid, Saad S. Mahmood, Yaseen A. OraibiThe aim of this paper is to design feed forward artificial neural network Ann to estimate two dimensional Henon dynamical map by selecting an appropriate network, transfer function and node weights. The proposed network side by side with using Fast Fourier Transform FFT as transfer function is used. For different cases of the system, chaotic and noisy,...

Keywords: network, design, node, neural network
Artificial Neural Networks Explore Color Naming System Similar To Humans
https://www.marktechpost.com/ | Yesterday
Content: Language is probably humanity 8217 s most distinguishing attribute, but we still don 8217 t wholly comprehend many of its fundamental properties, for instance, how it evolved to be such an efficient system. Facebook Artificial Intelligence AI models attempted to recreate the exact circumstances and communication processes to imitate natural behavior to better understand this. Let 8217 s dig into what 8230 The post Artificial Neural Networks Explore Color Naming System Similar To Humans...

Keywords: network, ai , neural network
Deep Learning model to maximize lifespan after liver transplant - Medical Xpress
https://medicalxpress.com/ | Yesterday
Content: Deep Learning model to maximize lifespan after liver transplantMedical Xpress...

Keywords: deep learning
Elden Ring's "Final Boss" Generated By Neural Network - Screen Rant
https://screenrant.com/ | Today
Content: Elden Ring s Final Boss Generated By Neural Network Screen Rant...

Keywords: neural network, network
Pexip to Study AI, Deep Learning Via NVIDIA GPU-Accelerated AI Software - rAVe [PUBS]
https://www.ravepubs.com/ | Yesterday
Content: Pexip to Study AI, Deep Learning Via NVIDIA GPU Accelerated AI SoftwarerAVe PUBS...

Keywords: deep learning, ai , gpu
Sparse Coding Frontend for Robust Neural Networks
https://paperswithcode.com/ | Yesterday
Content: Deep Neural Networks are known to be vulnerable to small, adversarially crafted, perturbations. Code...

Keywords: network, neural network, coding
Static Hand Gesture Recognition Using Multi-Layer Neural Network Classifier on Hybrid of Features
http://article.sapub.org/ | Yesterday
Content: Publication year 2020Source American Journal of Intelligent Systems, Volume 10, Number 1Akintola K. G., Emmanuel J. A.Hand gesture recognition has gotten so many areas of application such as in human computer interaction, hearing impaired communication and systems control. Recognizing gestures in videos however is challenging task. Many techniques and features have been adopted in the literature but some of the methods still need to be improved upon. There are basically two types of gestur...

Keywords: test, neural network, network, classification
Understanding Recurrent Neural Networks Using Nonequilibrium Response Theory
http://jmlr.org/ | Today
Content: Recurrent neural networks RNNs are brain inspired models widely used in machine learning for analyzing sequential data. The present work is contribution towards deeper understanding of how RNNs process input signals using the response theory from nonequilibrium statistical mechanics. For class of continuous time stochastic RNNs SRNNs driven by an input signal, we derive Volterra type series representation for their output. This representation is interpretable and disentangles the...

Keywords: machine learning, neural network, statistic
Autoencoder Anomaly Detection Using PyTorch - Visual Studio Magazine
https://visualstudiomagazine.com/ | Yesterday
Content: Autoencoder Anomaly Detection Using PyTorch Visual Studio Magazine...

Keywords: visual, pytorch
Neural Network Software 2021 Future Growth Insight | Google, IBM Corporation, Microsoft, Intel Corporatio...
https://ksusentinel.com/ | Yesterday
Content: Neural Network Software 2021 Future Growth Insight Google, IBM Corporation, Microsoft, Intel Corporation, Oracle, SAP SE, Qualcomm Technologies, Inc., KSU The Sentinel NewspaperKSU The Sentinel Newspaper...

Keywords: network, neural network
A Bop and Beyond: A Second Order Optimizer for Binarized Neural Networks
https://paperswithcode.com/ | Yesterday
Content: Current techniques for weight updating use the same approaches as traditional Neural Networks NNs with the extra requirement of using an approximation to the derivative of the sign function as it is the Dirac Delta function for back propagation thus, efforts are focused adapting full precision techniques to work on BNNs. Code href...

Keywords: neural network, network
The World as a Graph: Improving El Nio Forecasts with Graph Neural Networks
https://paperswithcode.com/ | Yesterday
Content: In comparison, graph neural networks GNNs are capable of modeling large scale spatial dependencies and are more interpretable due to the explicit modeling of information flow through edge connections. Code href...

Keywords: neural network, network, graph neural
Deeplite raises $7.5 million CAD seed round to optimize deep neural networks - BetaKit
https://betakit.com/ | Yesterday
Content: Deeplite raises 7.5 million CAD seed round to optimize deep neural networks BetaKit Deeplite raises 6M seed to deploy ML on edge with fewer compute resources TechCrunch View Full coverage on Google News...

Keywords: network, neural network, startup
A Visualizer for PyTorch Image Transformations
https://m.mage.ai/ | Today
Content: Visualizer for PyTorch Image Transformations...

Keywords: visual, pytorch
PyTorch vs. TensorFlow a detailed comparison
https://www.tooploox.com/ | Yesterday
Content: PyTorch vs. TensorFlow detailed comparison...

Keywords: tensorflow, pytorch
Text Classification using Transformers in PyTorch
http://www.datatau.com/ | Yesterday
Content: Text Classification using Transformers in PyTorch...

Keywords: pytorch, classification, transformer
An Efficient 2D Method for Training Super-Large Deep Learning Models
https://paperswithcode.com/ | Today
Content: However, due to memory constraints, model parallelism must be utilized to host large models that would otherwise not fit into the memory of single device. Code href...

Keywords: deep learning
Someone Used Neural Networks To Upscale Footage Of Denmark From 1902 And It's Like Stepping Out Of A Time...
https://digg.com/ | Yesterday
Content: scene from 1902 in Aarhus, Denmark is enhanced to look like if it was filmed today....

Keywords: neural network, network
Adversarial Attacks For Fooling Deep Neural Networks
https://neurosys.com/ | Yesterday
Content: Adversarial Attacks For Fooling Deep Neural Networks...

Keywords: neural network, network
Deep learning on dynamic graphs
https://blog.twitter.com/ | Yesterday
Content: Deep learning on dynamic graphs...

Keywords: deep learning, neural network, network
On Robustness and Transferability of Convolutional Neural Networks
https://research.google/ | Yesterday
Content: Modern deep convolutional networks CNNs are often criticized for their failure to generalize under distributional shifts. However, several recent breakthroughs in transfer learning suggest that these networks can cope with severe distribution shifts and successfully adapt to new tasks from few training examples. In this work we revisit the out of distribution and transfer performance of......

Keywords: network, transfer learning, neural network
This Research Paper From Google Research Proposes A Message Passing Graph Neural Network That Explicitly ...
https://www.marktechpost.com/ | Yesterday
Content: Recently, Computer vision CV research driven by Deep Learning has achieved significant progress in classifying video clips taken from the Internet and analyzing human actions in them. These video based tasks can be pretty challenging, as they require an understanding of the interactions between humans, objects, the context within given scene. It also requires an understanding 8230 The post appeared first on rel nofollow href...

Keywords: computer vision, network, deep learning
ICYMI: New AI Tools and Technologies Announced at GTC 2021 Keynote
https://developer.nvidia.com/ | Yesterday
Content: NVIDIA announced new software tools to help developers build optimized conversational AI, recommender, and video solutions. At GTC 2021, NVIDIA announced new software tools to help developers build optimized conversational AI, recommender, and video solutions. Watch the keynote from CEO, Jensen Huang, for insights on all of the latest GPU technologies.Announcing Availability of NVIDIA JarvisToday NVIDIA announced major conversational AI capabilities in NVIDIA Jarvis that will help enterprises bu...

Keywords: tensorflow, cpu, network, pytorch, quant
Title
Banach Space Representer Theorems for Neural Networks and Ridge Splines
http://jmlr.org/ | Today   

Keywords: design, framework, network, neural network   

Support Vector Machines vs Multiplicative Neuron Model Neural Network in Prediction of Bank Failures
http://article.sapub.org/ | Yesterday   

Keywords: metric, ios, algorithms, neural network   

Phase Diagram for Two-layer ReLU Neural Networks at Infinite-width Limit
http://jmlr.org/ | Today   

Keywords: network, neural network, statistic   

Why Choose Deep Learning
https://www.youtube.com/ | Yesterday   

Keywords: deep learning, matlab   

Neural Networks as Geometric Chaotic Maps
https://arxiv.org | Yesterday   

Keywords: metric, network, neural network   

A State-of-the-art Survey of Artificial Neural Networks for Whole-slide Image Analysis:from Popular Convo...
https://arxiv.org | Yesterday   

Keywords: metric, r , neural network   

Anomaly Detection in Image Datasets Using Convolutional Neural Networks, Center Loss, and Mahalanobis Distance
https://arxiv.org | Yesterday   

Keywords: neural network, network, analysis, classification   

Bayesian Optimisation for a Biologically Inspired Population Neural Network
https://arxiv.org | Yesterday   

Keywords: tpu, network, neural network   

Self-supervised Auxiliary Learning for Graph Neural Networks via Meta-Learning
https://arxiv.org | Yesterday   

Keywords: neural network, natural language processing   

A Deep Learning Architecture for Conservative Dynamical Systems: Application to Rainfall-Runoff Modeling
https://research.google/ | Yesterday   

Keywords: tpu, deep learning, network   

Computer Scientists From Rice University Display CPU Algorithm That Trains Deep Neural Networks 15 Times ...
https://www.marktechpost.com/ | Yesterday   

Keywords: cpu, network, ai , neural   

Large Data Analysis via Interpolation of Functions: Interpolating Polynomials vs Artificial Neural Networks
http://article.sapub.org/ | Yesterday   

Keywords: network, data analysis, analysis, neural   

Global Convergence of Second-order Dynamics in Two-layer Neural Networks
https://research.google/ | Yesterday   

Keywords: neural network, network   

Fusion of convolution neural network, support vector machine and Sobel filter for accurate detection of C...
https://www.docwirenews.com/ | Yesterday   

Keywords: neural network, network   

Knowing More about Neural Networks
https://networking.cioreview.com/ | Today   

Keywords: design, test, turing, visual, network   

Researchers At The University Of Houston Propose A New Artificial Neural Network Design That Can Differen...
https://www.marktechpost.com/ | Yesterday   

Keywords: ai , test, mobile, classification   

404.zero utilise neural networks and analog synthesisers in Deep Echo - FACT
https://www.factmag.com/ | Today   

Keywords: network, neural network   

The Convex Relaxation Barrier, Revisited: Tightened Single-Neuron Relaxations for Neural Network Verification
https://research.google/ | Yesterday   

Keywords: neural network, network, algorithms   

Machine Learning and AI Neural Networks at Work in Blue Ridge Price Optimization - Press Release - Digita...
http://www.digitaljournal.com/ | Yesterday   

Keywords: neural network, network, machine learning   

MicroNets: Neural Network Architectures for Deploying TinyML Applications on Commodity Microcontrollers
https://arxiv.org | Yesterday   

Keywords: machine learning, design, neural network   

Explaining Neural Network Predictions on Sentence Pairs via Learning Word-Group Masks
https://arxiv.org | Yesterday   

Keywords: bert , neural network, computing   

Self-adaptive loss balanced Physics-informed neural networks for the incompressible Navier-Stokes equations
https://arxiv.org | Yesterday   

Keywords: network, neural network   

Complex-Valued vs. Real-Valued Neural Networks for Classification Perspectives: An Example on Non-Circula...
https://arxiv.org | Yesterday   

Keywords: python library, neural network, python   

Vertically Federated Graph Neural Network for Privacy-Preserving Node Classification
https://arxiv.org | Yesterday   

Keywords: r , neural network, network   

Deep Learning model developed at UHN to maximize lifespan after liver transplant - EurekAlert
https://www.eurekalert.org/ | Yesterday   

Keywords: deep learning   

Autoencoder Anomaly Detection Using PyTorch
https://www.google.com/ | Yesterday   

Keywords: python, pytorch   

Balance Regularized Neural Network Models for Causal Effect Estimation
https://research.google/ | Yesterday   

Keywords: neural network, network   

Proposed Neural Network with FFT Transfer Function to Estimate Henon Dynamical Map
http://article.sapub.org/ | Yesterday   

Keywords: network, design, node, neural network   

Artificial Neural Networks Explore Color Naming System Similar To Humans
https://www.marktechpost.com/ | Yesterday   

Keywords: network, ai , neural network   

Deep Learning model to maximize lifespan after liver transplant - Medical Xpress
https://medicalxpress.com/ | Yesterday   

Keywords: deep learning   

Elden Ring's "Final Boss" Generated By Neural Network - Screen Rant
https://screenrant.com/ | Today   

Keywords: neural network, network   

Pexip to Study AI, Deep Learning Via NVIDIA GPU-Accelerated AI Software - rAVe [PUBS]
https://www.ravepubs.com/ | Yesterday   

Keywords: deep learning, ai , gpu   

Sparse Coding Frontend for Robust Neural Networks
https://paperswithcode.com/ | Yesterday   

Keywords: network, neural network, coding   

Static Hand Gesture Recognition Using Multi-Layer Neural Network Classifier on Hybrid of Features
http://article.sapub.org/ | Yesterday   

Keywords: test, neural network, network, classification   

Understanding Recurrent Neural Networks Using Nonequilibrium Response Theory
http://jmlr.org/ | Today   

Keywords: machine learning, neural network, statistic   

Autoencoder Anomaly Detection Using PyTorch - Visual Studio Magazine
https://visualstudiomagazine.com/ | Yesterday   

Keywords: visual, pytorch   

Neural Network Software 2021 Future Growth Insight | Google, IBM Corporation, Microsoft, Intel Corporatio...
https://ksusentinel.com/ | Yesterday   

Keywords: network, neural network   

A Bop and Beyond: A Second Order Optimizer for Binarized Neural Networks
https://paperswithcode.com/ | Yesterday   

Keywords: neural network, network   

The World as a Graph: Improving El Nio Forecasts with Graph Neural Networks
https://paperswithcode.com/ | Yesterday   

Keywords: neural network, network, graph neural   

Deeplite raises $7.5 million CAD seed round to optimize deep neural networks - BetaKit
https://betakit.com/ | Yesterday   

Keywords: network, neural network, startup   

A Visualizer for PyTorch Image Transformations
https://m.mage.ai/ | Today   

Keywords: visual, pytorch   

PyTorch vs. TensorFlow a detailed comparison
https://www.tooploox.com/ | Yesterday   

Keywords: tensorflow, pytorch   

Text Classification using Transformers in PyTorch
http://www.datatau.com/ | Yesterday   

Keywords: pytorch, classification, transformer   

An Efficient 2D Method for Training Super-Large Deep Learning Models
https://paperswithcode.com/ | Today   

Keywords: deep learning   

Someone Used Neural Networks To Upscale Footage Of Denmark From 1902 And It's Like Stepping Out Of A Time...
https://digg.com/ | Yesterday   

Keywords: neural network, network   

Adversarial Attacks For Fooling Deep Neural Networks
https://neurosys.com/ | Yesterday   

Keywords: neural network, network   

Deep learning on dynamic graphs
https://blog.twitter.com/ | Yesterday   

Keywords: deep learning, neural network, network   

On Robustness and Transferability of Convolutional Neural Networks
https://research.google/ | Yesterday   

Keywords: network, transfer learning, neural network   

This Research Paper From Google Research Proposes A Message Passing Graph Neural Network That Explicitly ...
https://www.marktechpost.com/ | Yesterday   

Keywords: computer vision, network, deep learning   

ICYMI: New AI Tools and Technologies Announced at GTC 2021 Keynote
https://developer.nvidia.com/ | Yesterday   

Keywords: tensorflow, cpu, network, pytorch, quant   






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