Papers
Neural Persistence: A Complexity Measure for Deep Neural Networks Using Algebraic Topology
Bastian Rieck, Matteo Togninalli, Christian Bock et al.
A Universal Music Translation Network
Noam Mor, Lior Wolf, Adam Polyak et al.
CBOW Is Not All You Need: Combining CBOW with the Compositional Matrix Space Model
Florian Mai, Lukas Galke, Ansgar Scherp
Adaptive Estimators Show Information Compression in Deep Neural Networks
Ivan Chelombiev, Conor Houghton, Cian O'Donnell
Universal Successor Features Approximators
Diana Borsa, Andre Barreto, John Quan et al.
Deep Convolutional Networks as shallow Gaussian Processes
Adrià Garriga-Alonso, Carl Edward Rasmussen, Laurence Aitchison
Accumulation Bit-Width Scaling For Ultra-Low Precision Training Of Deep Networks
Charbel Sakr, Naigang Wang, Chia-Yu Chen et al.
On the loss landscape of a class of deep neural networks with no bad local valleys
Quynh Nguyen, Mahesh Chandra Mukkamala, Matthias Hein
h-detach: Modifying the LSTM Gradient Towards Better Optimization
Bhargav Kanuparthi, Devansh Arpit, Giancarlo Kerg et al.
Adv-BNN: Improved Adversarial Defense through Robust Bayesian Neural Network
Xuanqing Liu, Yao Li, Chongruo Wu et al.
Variational Bayesian Phylogenetic Inference
Cheng Zhang, Frederick A. Matsen IV
Relational Forward Models for Multi-Agent Learning
Andrea Tacchetti, H. Francis Song, Pedro A. M. Mediano et al.
Generative predecessor models for sample-efficient imitation learning
Yannick Schroecker, Mel Vecerik, Jon Scholz
Deep Learning 3D Shapes Using Alt-az Anisotropic 2-Sphere Convolution
Min Liu, Fupin Yao, Chiho Choi et al.
Hyperbolic Attention Networks
Caglar Gulcehre, Misha Denil, Mateusz Malinowski et al.
Structured Neural Summarization
Patrick Fernandes, Miltiadis Allamanis, Marc Brockschmidt
Multilingual Neural Machine Translation with Knowledge Distillation
Xu Tan, Yi Ren, Di He et al.
Optimistic mirror descent in saddle-point problems: Going the extra (gradient) mile
Panayotis Mertikopoulos, Bruno Lecouat, Houssam Zenati et al.
Emergent Coordination Through Competition
Siqi Liu, Guy Lever, Josh Merel et al.
Meta-Learning Update Rules for Unsupervised Representation Learning
Luke Metz, Niru Maheswaranathan, Brian Cheung et al.
Knowledge Flow: Improve Upon Your Teachers
Iou-Jen Liu, Jian Peng, Alexander Schwing
How Important is a Neuron
Kedar Dhamdhere, Mukund Sundararajan, Qiqi Yan
Learning to Adapt in Dynamic, Real-World Environments through Meta-Reinforcement Learning
Anusha Nagabandi, Ignasi Clavera, Simin Liu et al.
Soft Q-Learning with Mutual-Information Regularization
Jordi Grau-Moya, Felix Leibfried, Peter Vrancx