Papers
11,015 papers found
How Important is a Neuron
Kedar Dhamdhere, Mukund Sundararajan, Qiqi Yan
How Powerful are Graph Neural Networks?
Keyulu Xu*, Weihua Hu*, Jure Leskovec et al.
How to train your MAML
Antreas Antoniou, Harrison Edwards, Amos Storkey
Human-level Protein Localization with Convolutional Neural Networks
Elisabeth Rumetshofer, Markus Hofmarcher, Clemens Röhrl et al.
Hyperbolic Attention Networks
Caglar Gulcehre, Misha Denil, Mateusz Malinowski et al.
Identifying and Controlling Important Neurons in Neural Machine Translation
Anthony Bau, Yonatan Belinkov, Hassan Sajjad et al.
ImageNet-trained CNNs are biased towards texture; increasing shape bias improves accuracy and robustness
Robert Geirhos, Patricia Rubisch, Claudio Michaelis et al.
Imposing Category Trees Onto Word-Embeddings Using A Geometric Construction
Tiansi Dong, Chrisitan Bauckhage, Hailong Jin et al.
Improving Differentiable Neural Computers Through Memory Masking, De-allocation, and Link Distribution Sharpness Control
Robert Csordas, Juergen Schmidhuber
Improving Generalization and Stability of Generative Adversarial Networks
Hoang Thanh-Tung, Truyen Tran, Svetha Venkatesh
Improving MMD-GAN Training with Repulsive Loss Function
Wei Wang, Yuan Sun, Saman Halgamuge
Improving Sequence-to-Sequence Learning via Optimal Transport
Liqun Chen, Yizhe Zhang, Ruiyi Zhang et al.
Improving the Generalization of Adversarial Training with Domain Adaptation
Chuanbiao Song, Kun He, Liwei Wang et al.
InfoBot: Transfer and Exploration via the Information Bottleneck
Anirudh Goyal, Riashat Islam, DJ Strouse et al.
Information asymmetry in KL-regularized RL
Alexandre Galashov, Siddhant M. Jayakumar, Leonard Hasenclever et al.
Information-Directed Exploration for Deep Reinforcement Learning
Nikolay Nikolov, Johannes Kirschner, Felix Berkenkamp et al.
Information Theoretic lower bounds on negative log likelihood
Luis A. Lastras-Montaño
Initialized Equilibrium Propagation for Backprop-Free Training
Peter O'Connor, Efstratios Gavves, Max Welling
InstaGAN: Instance-aware Image-to-Image Translation
Sangwoo Mo, Minsu Cho, Jinwoo Shin
Integer Networks for Data Compression with Latent-Variable Models
Johannes Ballé, Nick Johnston, David Minnen
Interpolation-Prediction Networks for Irregularly Sampled Time Series
Satya Narayan Shukla, Benjamin Marlin
Invariant and Equivariant Graph Networks
Haggai Maron, Heli Ben-Hamu, Nadav Shamir et al.
INVASE: Instance-wise Variable Selection using Neural Networks
Jinsung Yoon, James Jordon, Mihaela van der Schaar
Janossy Pooling: Learning Deep Permutation-Invariant Functions for Variable-Size Inputs
Ryan L. Murphy, Balasubramaniam Srinivasan, Vinayak Rao et al.
Kernel Change-point Detection with Auxiliary Deep Generative Models
Wei-Cheng Chang, Chun-Liang Li, Yiming Yang et al.