Visualizing the Loss Landscape of Neural Nets

28 December 2017

Hao Li

Papers citing "Visualizing the Loss Landscape of Neural Nets"

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Title
Review: Deep Learning in Electron Microscopy Jeffrey M. Ede 26 79 0 17 Sep 2020
Effective Federated Adaptive Gradient Methods with Non-IID Decentralized Data Qianqian Tong Guannan Liang J. Bi FedML 33 27 0 14 Sep 2020
Deforming the Loss Surface to Affect the Behaviour of the Optimizer Liangming Chen Long Jin Xiujuan Du Shuai Li Mei Liu ODL 8 2 0 14 Sep 2020
On the Orthogonality of Knowledge Distillation with Other Techniques: From an Ensemble Perspective Seonguk Park Kiyoon Yoo Nojun Kwak FedML 13 3 0 09 Sep 2020
Going deeper with brain morphometry using neural networks Rodrigo Santa Cruz Leo Lebrat Pierrick Bourgeat Vincent Doré Jason Dowling Jurgen Fripp Clinton Fookes Olivier Salvado 3DV MedIm 13 6 0 07 Sep 2020
S-SGD: Symmetrical Stochastic Gradient Descent with Weight Noise Injection for Reaching Flat Minima Wonyong Sung Iksoo Choi Jinhwan Park Seokhyun Choi Sungho Shin ODL 17 7 0 05 Sep 2020
Visualizing the Loss Landscape of Actor Critic Methods with Applications in Inventory Optimization Recep Yusuf Bekci M. Gümüş 12 4 0 04 Sep 2020
DARTS-: Robustly Stepping out of Performance Collapse Without Indicators Xiangxiang Chu Xiaoxing Wang Bo-Wen Zhang Shun Lu Xiaolin K. Wei Junchi Yan 4 161 0 02 Sep 2020
A Primer on Motion Capture with Deep Learning: Principles, Pitfalls and Perspectives Alexander Mathis Steffen Schneider Jessy Lauer Mackenzie W. Mathis 22 165 0 01 Sep 2020
Adversarially Robust Learning via Entropic Regularization Gauri Jagatap Ameya Joshi A. B. Chowdhury S. Garg C. Hegde OOD 25 11 0 27 Aug 2020
Likelihood Landscapes: A Unifying Principle Behind Many Adversarial Defenses Fu-Huei Lin Rohit Mittapalli Prithvijit Chattopadhyay Daniel Bolya Judy Hoffman AAML 40 2 0 25 Aug 2020
Prevention is Better than Cure: Handling Basis Collapse and Transparency in Dense Networks Gurpreet Singh Soumyajit Gupta Clint Dawson AI4CE 12 0 0 22 Aug 2020
DronePose: Photorealistic UAV-Assistant Dataset Synthesis for 3D Pose Estimation via a Smooth Silhouette Loss G. Albanis N. Zioulis A. Dimou D. Zarpalas P. Daras 3DH 17 10 0 20 Aug 2020
Neural Complexity Measures Yoonho Lee Juho Lee Sung Ju Hwang Eunho Yang Seungjin Choi 20 8 0 07 Aug 2020
Continuous-in-Depth Neural Networks A. Queiruga N. Benjamin Erichson D. Taylor Michael W. Mahoney 16 45 0 05 Aug 2020
A Neural-Symbolic Framework for Mental Simulation Michael D Kissner 14 0 0 05 Aug 2020
Analytic Characterization of the Hessian in Shallow ReLU Models: A Tale of Symmetry Yossi Arjevani M. Field 8 16 0 04 Aug 2020
Shallow Univariate ReLu Networks as Splines: Initialization, Loss Surface, Hessian, & Gradient Flow Dynamics Justin Sahs Ryan Pyle Aneel Damaraju J. O. Caro Onur Tavaslioglu Andy Lu Ankit B. Patel 11 19 0 04 Aug 2020
MLR-SNet: Transferable LR Schedules for Heterogeneous Tasks Jun Shu Yanwen Zhu Qian Zhao Zongben Xu Deyu Meng 18 7 0 29 Jul 2020
Deforming the Loss Surface Liangming Chen Long Jin Xiujuan Du Shuai Li Mei Liu ODL 6 0 0 24 Jul 2020
The Representation Theory of Neural Networks M. Armenta Pierre-Marc Jodoin 19 30 0 23 Jul 2020
Deep Learning Based Brain Tumor Segmentation: A Survey Zhihua Liu Lei Tong Zheheng Jiang Long Chen Feixiang Zhou Qianni Zhang Xiangrong Zhang Ling Li Huiyu Zhou 3DV 24 227 0 18 Jul 2020
Data-driven effective model shows a liquid-like deep learning Wenxuan Zou Haiping Huang 18 2 0 16 Jul 2020
Quantitative Propagation of Chaos for SGD in Wide Neural Networks Valentin De Bortoli Alain Durmus Xavier Fontaine Umut Simsekli 16 25 0 13 Jul 2020
RicciNets: Curvature-guided Pruning of High-performance Neural Networks Using Ricci Flow Samuel Glass Simeon E. Spasov Pietro Lió 12 5 0 08 Jul 2020
Model-based Clustering using Automatic Differentiation: Confronting Misspecification and High-Dimensional Data Siva Rajesh Kasa Vaibhav Rajan 9 0 0 08 Jul 2020
The Global Landscape of Neural Networks: An Overview Ruoyu Sun Dawei Li Shiyu Liang Tian Ding R. Srikant 20 82 0 02 Jul 2020
Persistent Neurons Yimeng Min 19 0 0 02 Jul 2020
Learn Faster and Forget Slower via Fast and Stable Task Adaptation Farshid Varno Lucas May Petry Lisa Di-Jorio Stan Matwin CLL 14 2 0 02 Jul 2020
Go Wide, Then Narrow: Efficient Training of Deep Thin Networks Denny Zhou Mao Ye Chen Chen Tianjian Meng Mingxing Tan Xiaodan Song Quoc V. Le Qiang Liu Dale Schuurmans 6 19 0 01 Jul 2020
On the Demystification of Knowledge Distillation: A Residual Network Perspective N. Jha Rajat Saini Sparsh Mittal 13 4 0 30 Jun 2020
Gradient-only line searches to automatically determine learning rates for a variety of stochastic training algorithms D. Kafka D. Wilke ODL 20 0 0 29 Jun 2020
Lipschitzness Is All You Need To Tame Off-policy Generative Adversarial Imitation Learning Lionel Blondé Pablo Strasser Alexandros Kalousis 25 22 0 28 Jun 2020
Smooth Adversarial Training Cihang Xie Mingxing Tan Boqing Gong Alan Yuille Quoc V. Le OOD 19 152 0 25 Jun 2020
Dynamic of Stochastic Gradient Descent with State-Dependent Noise Qi Meng Shiqi Gong Wei Chen Zhi-Ming Ma Tie-Yan Liu 6 16 0 24 Jun 2020
Learning Potentials of Quantum Systems using Deep Neural Networks Arijit Sehanobish H. Corzo Onur Kara David van Dijk 6 12 0 23 Jun 2020
IDF++: Analyzing and Improving Integer Discrete Flows for Lossless Compression Rianne van den Berg A. Gritsenko Mostafa Dehghani C. Sønderby Tim Salimans 19 59 0 22 Jun 2020
On the alpha-loss Landscape in the Logistic Model Tyler Sypherd Mario Díaz Lalitha Sankar Gautam Dasarathy 6 5 0 22 Jun 2020
MaxVA: Fast Adaptation of Step Sizes by Maximizing Observed Variance of Gradients Chenfei Zhu Yu Cheng Zhe Gan Furong Huang Jingjing Liu Tom Goldstein ODL 25 2 0 21 Jun 2020
On the Almost Sure Convergence of Stochastic Gradient Descent in Non-Convex Problems P. Mertikopoulos Nadav Hallak Ali Kavis V. Cevher 11 85 0 19 Jun 2020
FrostNet: Towards Quantization-Aware Network Architecture Search Taehoon Kim Y. Yoo Jihoon Yang MQ 17 2 0 17 Jun 2020
Learning Rates as a Function of Batch Size: A Random Matrix Theory Approach to Neural Network Training Diego Granziol S. Zohren Stephen J. Roberts ODL 29 48 0 16 Jun 2020
SPLASH: Learnable Activation Functions for Improving Accuracy and Adversarial Robustness Mohammadamin Tavakoli Forest Agostinelli Pierre Baldi AAML FAtt 22 39 0 16 Jun 2020
Feature Space Saturation during Training Mats L. Richter Justin Shenk Wolf Byttner Anders Arpteg Mikael Huss FAtt 11 6 0 15 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 19 81 0 15 Jun 2020
Understanding Global Loss Landscape of One-hidden-layer ReLU Networks, Part 2: Experiments and Analysis Bo Liu 8 1 0 15 Jun 2020
MetaPerturb: Transferable Regularizer for Heterogeneous Tasks and Architectures Jeongun Ryu Jaewoong Shin Haebeom Lee Sung Ju Hwang AAML OOD 14 8 0 13 Jun 2020
Is the Skip Connection Provable to Reform the Neural Network Loss Landscape? Lifu Wang Bo Shen Ningrui Zhao Zhiyuan Zhang 8 16 0 10 Jun 2020
Interpolation between Residual and Non-Residual Networks Zonghan Yang Yang Liu Chenglong Bao Zuoqiang Shi 12 11 0 10 Jun 2020
Extrapolation for Large-batch Training in Deep Learning Tao R. Lin Lingjing Kong Sebastian U. Stich Martin Jaggi 12 36 0 10 Jun 2020