| Aligning Visual Regions and Textual Concepts for Semantic-Grounded Image Representations | Fenglin Liu · Yuanxin Liu · Xuancheng Ren · Xiaodong He · Xu Sun |
| Augmented Neural ODEs | Emilien Dupont · Arnaud Doucet · Yee Whye Teh |
| Beyond Vector Spaces: Compact Data Representation as Differentiable Weighted Graphs | Denis Mazur · Vage Egiazarian · Stanislav Morozov · Artem Babenko |
| Exact Rate-Distortion in Autoencoders via Echo Noise | Rob Brekelmans · Daniel Moyer · Aram Galstyan · Greg Ver Steeg |
| Information Competing Process for Learning Diversified Representations | Jie Hu · Rongrong Ji · ShengChuan Zhang · Xiaoshuai Sun · Qixiang Ye · Chia-Wen Lin · Qi Tian |
| Learning low-dimensional state embeddings and metastable clusters from time series data | Yifan Sun · Yaqi Duan · Hao Gong · Mengdi Wang |
| Learning Nonsymmetric Determinantal Point Processes | Mike Gartrell · Victor-Emmanuel Brunel · Elvis Dohmatob · Syrine Krichene |
| Provably Powerful Graph Networks | Haggai Maron · Heli Ben-Hamu · Hadar Serviansky · Yaron Lipman |
| Quaternion Knowledge Graph Embeddings | SHUAI ZHANG · Yi Tay · Lina Yao · Qi Liu |
| Semi-supervisedly Co-embedding Attributed Networks | Zaiqiao Meng · Shangsong Liang · Jinyuan Fang · Teng Xiao |
| Large Scale Adversarial Representation Learning | Jeff Donahue · Karen Simonyan |
| Layer-Dependent Importance Sampling for Training Deep and Large Graph Convolutional Networks | Difan Zou · Ziniu Hu · Yewen Wang · Song Jiang · Yizhou Sun · Quanquan Gu |
| Learning elementary structures for 3D shape generation and matching | Theo Deprelle · Thibault Groueix · Matthew Fisher · Vladimir Kim · Bryan Russell · Mathieu Aubry |
| Learning from brains how to regularize machines | Zhe Li · Wieland Brendel · Edgar Walker · Erick Cobos · Taliah Muhammad · Jacob Reimer · Matthias Bethge · Fabian Sinz · Zachary Pitkow · Andreas Tolias |
| Rethinking Kernel Methods for Node Representation Learning on Graphs | Yu Tian · Long Zhao · Xi Peng · Dimitris Metaxas |
| Slice-based Learning: A Programming Model for Residual Learning in Critical Data Slices | Vincent Chen · Sen Wu · Alexander Ratner · Jen Weng · Christopher Ré |
| Deep Supervised Summarization: Algorithm and Application to Learning Instructions | Chengguang Xu · Ehsan Elhamifar |
| Unsupervised Emergence of Egocentric Spatial Structure from Sensorimotor Prediction | Alban Laflaquière · Michael Garcia Ortiz |
| Unsupervised State Representation Learning in Atari | Ankesh Anand · Evan Racah · Sherjil Ozair · Yoshua Bengio · Marc-Alexandre Côté · R Devon Hjelm |
| What the Vec? Towards Probabilistically Grounded Embeddings | Carl Allen · Ivana Balazevic · Timothy Hospedales |
| Are Disentangled Representations Helpful for Abstract Visual Reasoning? | Sjoerd van Steenkiste · Francesco Locatello · Jürgen Schmidhuber · Olivier Bachem |
| CPM-Nets: Cross Partial Multi-View Networks | Changqing Zhang · Zongbo Han · yajie cui · Huazhu Fu · Joey Tianyi Zhou · Qinghua Hu |
| Cross-lingual Language Model Pretraining | Alexis CONNEAU · Guillaume Lample |
| Graph Transformer Networks | Seongjun Yun · Minbyul Jeong · Raehyun Kim · Jaewoo Kang · Hyunwoo Kim |
| Learning Representations by Maximizing Mutual Information Across Views | Philip Bachman · R Devon Hjelm · William Buchwalter |
| Numerically Accurate Hyperbolic Embeddings Using Tiling-Based Models | Tao Yu · Christopher De Sa |
| On the Fairness of Disentangled Representations | Francesco Locatello · Gabriele Abbati · Thomas Rainforth · Stefan Bauer · Bernhard Schölkopf · Olivier Bachem |
| On the Transfer of Inductive Bias from Simulation to the Real World: a New Disentanglement Dataset | Muhammad Waleed Gondal · Manuel Wuthrich · Djordje Miladinovic · Francesco Locatello · Martin Breidt · Valentin Volchkov · Joel Akpo · Olivier Bachem · Bernhard Schölkopf · Stefan Bauer |
| Stacked Capsule Autoencoders | Adam Kosiorek · Sara Sabour · Yee Whye Teh · Geoffrey E Hinton |
| Understanding the Representation Power of Graph Neural Networks in Learning Graph Topology | Nima Dehmamy · Albert-Laszlo Barabasi · Rose Yu |
| Wasserstein Dependency Measure for Representation Learning | Sherjil Ozair · Corey Lynch · Yoshua Bengio · Aaron van den Oord · Sergey Levine · Pierre Sermanet |