Papers
11,951 papers found
On the Relationship between Self-Attention and Convolutional Layers
Jean-Baptiste Cordonnier, Andreas Loukas, Martin Jaggi
On the "steerability" of generative adversarial networks
Ali Jahanian*, Lucy Chai*, Phillip Isola
On the Variance of the Adaptive Learning Rate and Beyond
Liyuan Liu, Haoming Jiang, Pengcheng He et al.
On the Weaknesses of Reinforcement Learning for Neural Machine Translation
Leshem Choshen, Lior Fox, Zohar Aizenbud et al.
On Universal Equivariant Set Networks
Nimrod Segol, Yaron Lipman
Optimal Strategies Against Generative Attacks
Roy Mor, Erez Peterfreund, Matan Gavish et al.
Optimistic Exploration even with a Pessimistic Initialisation
Tabish Rashid, Bei Peng, Wendelin Boehmer et al.
Option Discovery using Deep Skill Chaining
Akhil Bagaria, George Konidaris
Order Learning and Its Application to Age Estimation
Kyungsun Lim, Nyeong-Ho Shin, Young-Yoon Lee et al.
Overlearning Reveals Sensitive Attributes
Congzheng Song, Vitaly Shmatikov
PAC Confidence Sets for Deep Neural Networks via Calibrated Prediction
Sangdon Park, Osbert Bastani, Nikolai Matni et al.
Padé Activation Units: End-to-end Learning of Flexible Activation Functions in Deep Networks
Alejandro Molina, Patrick Schramowski, Kristian Kersting
PairNorm: Tackling Oversmoothing in GNNs
Lingxiao Zhao, Leman Akoglu
Pay Attention to Features, Transfer Learn Faster CNNs
Kafeng Wang, Xitong Gao, Yiren Zhao et al.
PC-DARTS: Partial Channel Connections for Memory-Efficient Architecture Search
Yuhui Xu, Lingxi Xie, Xiaopeng Zhang et al.
PCMC-Net: Feature-based Pairwise Choice Markov Chains
Alix Lhéritier
Penalized Langevin dynamics with vanishing penalty for smooth and log-concave targets
Avetik Karagulyan, Arnak Dalalyan
Permutation Equivariant Models for Compositional Generalization in Language
Jonathan Gordon, David Lopez-Paz, Marco Baroni et al.
Phase Transitions for the Information Bottleneck in Representation Learning
Tailin Wu, Ian Fischer
Physics-as-Inverse-Graphics: Unsupervised Physical Parameter Estimation from Video
Miguel Jaques, Michael Burke, Timothy Hospedales
Physics-aware Difference Graph Networks for Sparsely-Observed Dynamics
Sungyong Seo*, Chuizheng Meng*, Yan Liu
Picking Winning Tickets Before Training by Preserving Gradient Flow
Chaoqi Wang, Guodong Zhang, Roger Grosse
Piecewise linear activations substantially shape the loss surfaces of neural networks
Fengxiang He, Bohan Wang, Dacheng Tao
Pitch Declination and Final Lowering in Northeastern Mandarin
Ping Cui, Jianjing Kuang
Pitfalls of In-Domain Uncertainty Estimation and Ensembling in Deep Learning
Arsenii Ashukha, Alexander Lyzhov, Dmitry Molchanov et al.