Papers
Convolutional Neural Networks on Non-uniform Geometrical Signals Using Euclidean Spectral Transformation
Chiyu Max Jiang, Dequan Wang, Jingwei Huang et al.
Understanding Straight-Through Estimator in Training Activation Quantized Neural Nets
Penghang Yin, Jiancheng Lyu, Shuai Zhang et al.
Per-Tensor Fixed-Point Quantization of the Back-Propagation Algorithm
Charbel Sakr, Naresh Shanbhag
RotDCF: Decomposition of Convolutional Filters for Rotation-Equivariant Deep Networks
Xiuyuan Cheng, Qiang Qiu, Robert Calderbank et al.
Large Scale Graph Learning From Smooth Signals
Vassilis Kalofolias, Nathanaël Perraudin
L2-Nonexpansive Neural Networks
Haifeng Qian, Mark N. Wegman
Generating Liquid Simulations with Deformation-aware Neural Networks
Lukas Prantl, Boris Bonev, Nils Thuerey
Adversarial Imitation via Variational Inverse Reinforcement Learning
Ahmed H. Qureshi, Byron Boots, Michael C. Yip
Understanding and Improving Interpolation in Autoencoders via an Adversarial Regularizer
David Berthelot*, Colin Raffel*, Aurko Roy et al.
Learning Localized Generative Models for 3D Point Clouds via Graph Convolution
Diego Valsesia, Giulia Fracastoro, Enrico Magli
Caveats for information bottleneck in deterministic scenarios
Artemy Kolchinsky, Brendan D. Tracey, Steven Van Kuyk
A Kernel Random Matrix-Based Approach for Sparse PCA
Mohamed El Amine Seddik, Mohamed Tamaazousti, Romain Couillet
The relativistic discriminator: a key element missing from standard GAN
Alexia Jolicoeur-Martineau
INVASE: Instance-wise Variable Selection using Neural Networks
Jinsung Yoon, James Jordon, Mihaela van der Schaar
Opportunistic Learning: Budgeted Cost-Sensitive Learning from Data Streams
Mohammad Kachuee, Orpaz Goldstein, Kimmo Kärkkäinen et al.
Adversarial Reprogramming of Neural Networks
Gamaleldin F. Elsayed, Ian Goodfellow, Jascha Sohl-Dickstein
DARTS: Differentiable Architecture Search
Hanxiao Liu, Karen Simonyan, Yiming Yang
DPSNet: End-to-end Deep Plane Sweep Stereo
Sunghoon Im, Hae-Gon Jeon, Stephen Lin et al.
Diffusion Scattering Transforms on Graphs
Fernando Gama, Alejandro Ribeiro, Joan Bruna
Post Selection Inference with Incomplete Maximum Mean Discrepancy Estimator
Makoto Yamada, Denny Wu, Yao-Hung Hubert Tsai et al.
Hierarchical interpretations for neural network predictions
Chandan Singh, W. James Murdoch, Bin Yu
Dynamic Sparse Graph for Efficient Deep Learning
Liu Liu, Lei Deng, Xing Hu et al.
Learning to Understand Goal Specifications by Modelling Reward
Dzmitry Bahdanau, Felix Hill, Jan Leike et al.