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Samy Bengio
Spectrally-Based Audio Distances Are Bad at Pitch
Arxiv:2008.01352V3 [Cs.LG] 23 Mar 2021 Spatiotemporal Disentanglement in the PDE Formalism
Large Margin Deep Networks for Classification
Generative Adversarial Transformers
Adversarial Examples in the Physical World
Arxiv:1611.08903V1 [Cs.LG] 27 Nov 2016 20 Percent Increases in Cash Collections [20]
Submission Data for 2020-2021 CORE Conference Ranking Process International Conference on Learning Representations
Magmadnn: Accelerated Deep Learning Using MAGMA
Neurips 2020 Competition: Predicting Generalization in Deep Learning (Version 1.1)
Neural Network Tools: an Overview from Work on "Automatic Classification of Alzheimer’S Disease from Structural MRI" Report for Master’S Thesis
Inductive Biases for Deep Learning of Higher-Level Cognition
Accelerating Machine Learning Research with MI-Prometheus
To Text-Based Games
An Empirical Study of Example Forgetting During Deep Neural Network Learning
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The Scientific Method in the Science of Ma- Chine Learning
Arxiv:1604.00981V3 [Cs.LG] 21 Mar 2017 with Only a Subset of Worker Machines, Thus Alleviating the Straggler Effect While Avoiding Any Staleness in Our Gradients
Training Stronger Baselines for Learning to Optimize
Top View
Shanmukha Ramakrishna Vedantam 820 West Marietta Street NW, Apt 1145, Atlanta, GA, USA +1-334-329-9834 •
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Model Inversion Networks for Model-Based Optimization
Arxiv:1605.08803V3 [Cs.LG] 27 Feb 2017 This Model Can Perform Efficient and Exact Inference, Sampling and Log-Density Estimation of Data Points
Pytorch: an Imperative Style, High-Performance Deep Learning Library
Adversarial Machine Learning at Scale
Why Does Unsupervised Pre-Training Help Deep Learning?
Knowledge Matters: Importance of Prior Information for Optimization
Understanding Deep Learning Requires Rethinking Generalization
Learning to Remember Rare Events
Arxiv:2012.02775V1 [Cs.LG] 4 Dec 2020
Adversarial Machine Learning in Image Classification: a Survey Towards the Defender’S Perspective
Tensorlayer: a Versatile Library for Efficient Deep Learning Development
Guest Editors' Introduction: Special Section On
Yoshua Bengio
[email protected]
Arxiv:1809.02591V2 [Cs.LG] 12 Dec 2020
Defeating the Curse of Dimensionality to Scale JIT Fusion
Deep Learning
Pytorch: an Imperative Style, High-Performance Deep Learning Library
ML Project Multi-Step Generation of Chord Progressions for Inference in Jazz Through Recurrent Neural Networks
Yoshua Bengio
[email protected]
Methods and Analysis of the First Competition in Predicting Generalization of Deep Learning
Adversarial Attacks and Defenses: an Interpretation Perspective
Introduction to Machine Learning Deep Learning Applications
Adversarial Machine Learning at Scale