Sensitivity and Generalization in Neural Networks: an Empirical Study

23 February 2018

Jascha Narain Sohl-Dickstein

AAML

ArXiv PDF HTML

Papers citing "Sensitivity and Generalization in Neural Networks: an Empirical Study"

43 / 93 papers shown

Title
Meta-Learning Requires Meta-Augmentation Janarthanan Rajendran A. Irpan Eric Jang 24 93 0 10 Jul 2020
Learning Differential Equations that are Easy to Solve Jacob Kelly J. Bettencourt Matthew J. Johnson David Duvenaud 32 111 0 09 Jul 2020
Interpreting and Disentangling Feature Components of Various Complexity from DNNs Jie Ren Mingjie Li Zexu Liu Quanshi Zhang CoGe 19 18 0 29 Jun 2020
Riemannian Continuous Normalizing Flows Emile Mathieu Maximilian Nickel AI4CE 27 119 0 18 Jun 2020
What Do Neural Networks Learn When Trained With Random Labels? Hartmut Maennel Ibrahim M. Alabdulmohsin Ilya O. Tolstikhin R. Baldock Olivier Bousquet Sylvain Gelly Daniel Keysers FedML 48 87 0 18 Jun 2020
On the Loss Landscape of Adversarial Training: Identifying Challenges and How to Overcome Them Chen Liu Mathieu Salzmann Tao R. Lin Ryota Tomioka Sabine Süsstrunk AAML 24 81 0 15 Jun 2020
Dataless Model Selection with the Deep Frame Potential Calvin Murdock Simon Lucey 38 6 0 30 Mar 2020
Classifying the classifier: dissecting the weight space of neural networks Gabriel Eilertsen Daniel Jonsson Timo Ropinski Jonas Unger Anders Ynnerman 4 53 0 13 Feb 2020
How to train your neural ODE: the world of Jacobian and kinetic regularization Chris Finlay J. Jacobsen L. Nurbekyan Adam M. Oberman 11 296 0 07 Feb 2020
Optimized Generic Feature Learning for Few-shot Classification across Domains Tonmoy Saikia Thomas Brox Cordelia Schmid VLM 30 48 0 22 Jan 2020
Empirical Studies on the Properties of Linear Regions in Deep Neural Networks Xiao Zhang Dongrui Wu 21 38 0 04 Jan 2020
Mining Domain Knowledge: Improved Framework towards Automatically Standardizing Anatomical Structure Nomenclature in Radiotherapy Qiming Yang H. Chao D. Nguyen Steve B. Jiang 6 7 0 04 Dec 2019
Tensor Programs I: Wide Feedforward or Recurrent Neural Networks of Any Architecture are Gaussian Processes Greg Yang 33 193 0 28 Oct 2019
Improved Sample Complexities for Deep Networks and Robust Classification via an All-Layer Margin Colin Wei Tengyu Ma AAML OOD 36 85 0 09 Oct 2019
Needles in Haystacks: On Classifying Tiny Objects in Large Images Nick Pawlowski Suvrat Bhooshan Nicolas Ballas F. Ciompi Ben Glocker M. Drozdzal 24 22 0 16 Aug 2019
Dimensionality compression and expansion in Deep Neural Networks Stefano Recanatesi M. Farrell Madhu S. Advani Timothy Moore Guillaume Lajoie E. Shea-Brown 26 72 0 02 Jun 2019
On Network Design Spaces for Visual Recognition Ilija Radosavovic Justin Johnson Saining Xie Wan-Yen Lo Piotr Dollár 25 134 0 30 May 2019
Heterogeneous causal effects with imperfect compliance: a Bayesian machine learning approach Falco J. Bargagli-Stoffi Kristof De-Witte G. Gnecco 16 15 0 29 May 2019
SGD on Neural Networks Learns Functions of Increasing Complexity Preetum Nakkiran Gal Kaplun Dimitris Kalimeris Tristan Yang Benjamin L. Edelman Fred Zhang Boaz Barak MLT 14 236 0 28 May 2019
Scaleable input gradient regularization for adversarial robustness Chris Finlay Adam M. Oberman AAML 16 77 0 27 May 2019
Minimal Achievable Sufficient Statistic Learning Milan Cvitkovic Günther Koliander 25 12 0 19 May 2019
Data-dependent Sample Complexity of Deep Neural Networks via Lipschitz Augmentation Colin Wei Tengyu Ma 25 109 0 09 May 2019
Wide Neural Networks of Any Depth Evolve as Linear Models Under Gradient Descent Jaehoon Lee Lechao Xiao S. Schoenholz Yasaman Bahri Roman Novak Jascha Narain Sohl-Dickstein Jeffrey Pennington 34 1,077 0 18 Feb 2019
Parameter Efficient Training of Deep Convolutional Neural Networks by Dynamic Sparse Reparameterization Hesham Mostafa Xin Wang 37 307 0 15 Feb 2019
Stiffness: A New Perspective on Generalization in Neural Networks Stanislav Fort Pawel Krzysztof Nowak Stanislaw Jastrzebski S. Narayanan 21 94 0 28 Jan 2019
Frequency Principle: Fourier Analysis Sheds Light on Deep Neural Networks Zhi-Qin John Xu Yaoyu Zhang Tao Luo Yan Xiao Zheng Ma 17 503 0 19 Jan 2019
Three Mechanisms of Weight Decay Regularization Guodong Zhang Chaoqi Wang Bowen Xu Roger C. Grosse 11 256 0 29 Oct 2018
Bayesian Deep Convolutional Networks with Many Channels are Gaussian Processes Roman Novak Lechao Xiao Jaehoon Lee Yasaman Bahri Greg Yang Jiri Hron Daniel A. Abolafia Jeffrey Pennington Jascha Narain Sohl-Dickstein UQCV BDL 25 307 0 11 Oct 2018
Detecting Memorization in ReLU Networks Edo Collins Siavash Bigdeli Sabine Süsstrunk 36 4 0 08 Oct 2018
Why do Larger Models Generalize Better? A Theoretical Perspective via the XOR Problem Alon Brutzkus Amir Globerson MLT 16 7 0 06 Oct 2018
Choose Your Neuron: Incorporating Domain Knowledge through Neuron-Importance Ramprasaath R. Selvaraju Prithvijit Chattopadhyay Mohamed Elhoseiny Tilak Sharma Dhruv Batra Devi Parikh Stefan Lee 38 35 0 08 Aug 2018
Generalization Error in Deep Learning Daniel Jakubovitz Raja Giryes M. Rodrigues AI4CE 32 109 0 03 Aug 2018
PCA of high dimensional random walks with comparison to neural network training J. Antognini Jascha Narain Sohl-Dickstein OOD 24 27 0 22 Jun 2018
On the Spectral Bias of Neural Networks Nasim Rahaman A. Baratin Devansh Arpit Felix Dräxler Min Lin Fred Hamprecht Yoshua Bengio Aaron Courville 57 1,395 0 22 Jun 2018
Data augmentation instead of explicit regularization Alex Hernández-García Peter König 30 141 0 11 Jun 2018
A Simple Cache Model for Image Recognition Emin Orhan VLM 22 30 0 21 May 2018
Learning Representations for Neural Network-Based Classification Using the Information Bottleneck Principle Rana Ali Amjad Bernhard C. Geiger 35 196 0 27 Feb 2018
Understanding and Enhancing the Transferability of Adversarial Examples Lei Wu Zhanxing Zhu Cheng Tai E. Weinan AAML SILM 30 96 0 27 Feb 2018
Is Generator Conditioning Causally Related to GAN Performance? Augustus Odena Jacob Buckman Catherine Olsson Tom B. Brown C. Olah Colin Raffel Ian Goodfellow AI4CE 35 112 0 23 Feb 2018
Gradient Regularization Improves Accuracy of Discriminative Models D. Varga Adrián Csiszárik Zsolt Zombori 18 53 0 28 Dec 2017
Adversarial Machine Learning at Scale Alexey Kurakin Ian Goodfellow Samy Bengio AAML 296 3,113 0 04 Nov 2016
On Large-Batch Training for Deep Learning: Generalization Gap and Sharp Minima N. Keskar Dheevatsa Mudigere J. Nocedal M. Smelyanskiy P. T. P. Tang ODL 308 2,892 0 15 Sep 2016
The Loss Surfaces of Multilayer Networks A. Choromańska Mikael Henaff Michaël Mathieu Gerard Ben Arous Yann LeCun ODL 183 1,186 0 30 Nov 2014