📰 ICLR 2019: all accepted papers

52 papers · the most cited first · ← ICLR 2019

1. Music Transformer: Generating Music with Long-Term Structure ↗Cheng-Zhi Anna Huang, Ashish Vaswani, Jakob Uszkoreit et al.292 citations
2. DyRep: Learning Representations over Dynamic Graphs ↗Rakshit Trivedi, Mehrdad Farajtabar, Prasenjeet Biswal et al.210 citations
3. Eidetic 3D LSTM: A Model for Video Prediction and Beyond ↗Yunbo Wang, Lu Jiang, Ming Hsuan Yang et al.179 citations
4. Supervised community detection with line graph neural networks ↗Zhengdao Chen, Lisha Li, Joan Bruna99 citations
5. OVERCOMING CATASTROPHIC FORGETTING FOR CONTINUAL LEARNING VIA MODEL ADAPTATION ↗Wenpeng Hu, Lin Zhou, Bing Liu et al.72 citations
6. Understanding Posterior Collapse in Generative Latent Variable Models ↗James Lucas, George Tucker, Roger Grosse et al.72 citations
7. Integer Networks for Data Compression with Latent-Variable Models ↗Johannes Ballé, Nick Johnston, David C. Minnen51 citations
8. FVD: A new Metric for Video Generation ↗Thomas Unterthiner, Sjoerd van Steenkiste, Karol Kurach et al.43 citations
9. Fully differentiable full-atom protein backbone generation ↗Namrata Anand, Raphael R. Eguchi, Po‐Ssu Huang38 citations
10. Variational Autoencoder with Arbitrary Conditioning ↗О. А. Иванов, Michael Figurnov, Dmitry Vetrov37 citations
11. A new dog learns old tricks: RL finds classic optimization algorithms ↗Weiwei Kong, Christopher Liaw, Aranyak Mehta et al.28 citations
12. Buy 4 REINFORCE Samples, Get a Baseline for Free! ↗Wouter Kool, Herke van Hoof, Max Welling25 citations
13. Probgan: Towards probabilistic GaN with theoretical guarantees ↗Hao He, Hao Wang, Guang He Lee et al.23 citations
14. A Data-Driven and Distributed Approach to Sparse Signal Representation and Recovery ↗Ali Mousavi, Gautam Dasarathy, Richard G. Baraniuk18 citations
15. On Computation and Generalization of Generative Adversarial Networks under Spectrum Control ↗Haoming Jiang, Zhehui Chen, Minshuo Chen et al.16 citations
16. Generating Diverse High-Resolution Images with VQ-VAE ↗Ali Shervin Razavi, Aäron van den Oord, Oriol Vinyals14 citations
17. Efficient and Robust Asynchronous Federated Learning with Stragglers ↗Ming Chen, Bingcheng Mao, Tianyi Ma11 citations
18. Hierarchical RL Using an Ensemble of Proprioceptive Periodic Policies ↗Kenneth Marino, Abhinav Gupta, Rob Fergus et al.10 citations
19. Minigo: A Case Study in Reproducing Reinforcement Learning Research. ↗Brian Lee, Andrew Jackson, T. Madams et al.9 citations
20. Robust Reinforcement Learning for Autonomous Driving ↗Yesmina Jaafra, Jean Luc Laurent, Aline Deruyver et al.9 citations
21. Random mesh projectors for inverse problems ↗Konik Kothari, Sidharth Gupta, Maarten V. de Hoop et al.8 citations
22. Learning to Defense by Learning to Attack. ↗Zhehui Chen, Haoming Jiang, Yuyang Shi et al.6 citations
23. Interactive Visual Exploration of Latent Space (IVELS) for Peptide Auto-Encoder Model Selection ↗Tom Sercu, Sebastian Gehrmann, Hendrik Strobelt et al.5 citations
24. Smoothing Nonlinear Variational Objectives with Sequential Monte Carlo ↗Antonio Khalil Moretti, Zizhao Wang, Luhuan Wu et al.5 citations
25. Understanding the Relation Between Maximum-Entropy Inverse Reinforcement Learning and Behaviour Cloning. ↗Seyed Kamyar Seyed Ghasemipour, Shane Gu, Richard S. Zemel5 citations
26. simple_rl: Reproducible Reinforcement Learning in Python. ↗David Lynn Abel5 citations
27. On the relationship between Normalising Flows and Variational- and Denoising Autoencoders. ↗Alexey A. Gritsenko, Jasper Snoek, Tim Salimans4 citations
28. Reproducing Meta-learning with differentiable closed-form solvers. ↗Arnout Devos, Sylvain Chatel, Matthias Grossglauser4 citations
29. Deep Generative Models for Generating Labeled Graphs. ↗Shuangfei Fan, Bert Huang3 citations
30. Reproducibility and Stability Analysis in Metric-Based Few-Shot Learning. ↗Thomas Boquet, Laure Delisle, Denis Kochetkov et al.3 citations
31. AlignFlow: Learning from multiple domains via normalizing flows. ↗Aditya Grover, Chris Chute, Rui Shu et al.2 citations
32. Improved Adversarial Image Captioning ↗Pierre Dognin, Igor Melnyk, Youssef Mroueh et al.2 citations
33. Multi-agent query reformulation: Challenges and the role of diversity ↗Rodrigo Frassetto Nogueira, Jannis Bulian, Massimiliano Ciaramita2 citations
34. WiSE-ALE: Wide Sample Estimator for Aggregate Latent Embedding ↗Shu‐Yu Lin, Ronald Clark, Robert Birke et al.2 citations
35. A Seed-Augment-Train Framework for Universal Digit Classification ↗Vinay Uday Prabhu, Sanghyun Han, Dian Ang Yap et al.1 citation
36. Brief Report: Ordered Neurons: Integrating Tree Structures into Recurrent Neural Networks ↗Yikeng Shen, Shawn Tan, Alessandro Sordoni et al.1 citation
37. Compositional GAN (Extended Abstract): Learning Image-Conditional Binary Composition ↗Samaneh Azadi, Deepak Pathak, Sayna Ebrahimi et al.1 citation
38. Learning proposals for sequential importance samplers using reinforced variational inference. ↗Zafarali Ahmed, Arjun Karuvally, Doina Precup et al.1 citation
39. Revisiting Auxiliary Latent Variables in Generative Models. ↗Dieterich Lawson, George Tucker, Bo Dai et al.1 citation
40. Unsupervised Demixing of Structured Signals from Their Superposition Using GANs. ↗Mohammadreza Soltani, Swayambhoo Jain, Abhinav V. Sambasivan1 citation
41. Variational autoencoders trained with q-deformed lower bounds ↗Septimia Sârbu, Luigi Malagò1 citation
42. Visualizing and Understanding GANs ↗David Anthony Bau, Jun-Yan Zhu, Hendrik Strobelt et al.1 citation
43. ATLPA:ADVERSARIAL TOLERANT LOGIT PAIRING WITH ATTENTION FOR CONVOLUTIONAL NEURAL NETWORK ↗Dou Goodman
44. Artificial Design: Modeling Artificial Super Intelligence with Extended General Relativity and Universal Darwinism via Geometrization for Universal Design Automation ↗Yang Zhang
45. DUAL SPACE LEARNING WITH VARIATIONAL AUTOENCODERS ↗Hirono Okamoto, Masahiro Suzuki, Itto Higuchi et al.
46. Ensemble methods and LSTM outperformed other eight machine learning classifiers in an EEG-based BCI experiment ↗Xiaodong Qu, Zepeng Hu, Zhaonan Li et al.
47. Finite Automata Can be Linearly Decoded from Language-Recognizing RNNs ↗Joshua Michalenko, Ameesh Shah
48. Generative Integration Networks ↗Shohei Ohsawa
49. Learning Deep Latent-variable MRFs with Amortized Bethe Free Energy Minimization. ↗Sam Wiseman
50. Neural Program Planner for Structured Predictions. ↗Jacob Biloki, Liang Chen, Ni Lao
51. Resolving Lexical Ambiguity in English–Japanese Neural Machine Translation ↗Quang Le Minh, Incheon Paik
52. Smooth Regularized Reinforcement Learning ↗Haoming Jiang

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