Wasserstein Barycenter Model Ensembling
Comments ICLR 2019
期刊&会议
ICLR
International Conference on Learning Representations · 会议 · Machine Learning
Learning what you can do before doing anything
Comments Published at ICLR 2019. 10 pages + 15 pages of references and appendices
Journal ref International Conference on Learning Representations, 2019
Improving Generalization and Stability of Generative Adversarial Networks
Comments ICLR 2019
Multilingual Neural Machine Translation With Soft Decoupled Encoding
Comments accepted at ICLR 2019
CEM-RL: Combining evolutionary and gradient-based methods for policy search
Comments accepted at ICLR 2019
Adversarial Audio Synthesis
Comments Published as a conference paper at ICLR 2019
Minimal Images in Deep Neural Networks: Fragile Object Recognition in Natural Images
Comments International Conference on Learning Representations (ICLR) 2019
Improving MMD-GAN Training with Repulsive Loss Function
Comments Published as a conference paper at ICLR 2019
Learning to Propagate Labels: Transductive Propagation Network for Few-shot Learning
Comments Accepted in ICLR 2019; code available at https://github.com/csyanbin/TPN
Adaptive Posterior Learning: few-shot learning with a surprise-based memory module
Comments ICLR 2019
Attention, Learn to Solve Routing Problems!
Comments Accepted at ICLR 2019. 25 pages, 7 figures
L2-Nonexpansive Neural Networks
Journal ref International Conference on Learning Representations (ICLR), 2019
Learning to Schedule Communication in Multi-agent Reinforcement Learning
Comments Accepted in ICLR 2019
Gradient Descent Provably Optimizes Over-parameterized Neural Networks
Comments ICLR 2019
Generalized Tensor Models for Recurrent Neural Networks
Comments Accepted as a conference paper at ICLR 2019
No Training Required: Exploring Random Encoders for Sentence Classification
Comments Published as a conference paper at ICLR 2019
Lagging Inference Networks and Posterior Collapse in Variational Autoencoders
Comments ICLR 2019 Conference Paper
Deep Anomaly Detection with Outlier Exposure
Comments ICLR 2019; PyTorch code available at https://github.com/hendrycks/outlier-exposure
Guiding Policies with Language via Meta-Learning
Comments Accepted at ICLR 2019
Learning Actionable Representations with Goal-Conditioned Policies
Comments To be presented at ICLR 2019
Recall Traces: Backtracking Models for Efficient Reinforcement Learning
Comments Accepted at ICLR 2019
ICLR Reproducibility Challenge Report (Padam : Closing The Generalization Gap Of Adaptive Gradient Methods in Training Deep Neural Networks)
Comments ICLR Reproducibility Challenge 2019 Report for Padam (11 pages, 30 figures)
Variational Smoothing in Recurrent Neural Network Language Models
Comments Accepted as a conference paper at ICLR 2019
Plan Online, Learn Offline: Efficient Learning and Exploration via Model-Based Control
Comments The first two authors contributed equally. Accepted at ICLR 2019. Supplementary videos available at: https://sites.google.com/view/polo-mpc
Dynamic Channel Pruning: Feature Boosting and Suppression
Comments 14 pages, 5 figures, 4 tables, published as a conference paper at ICLR 2019
Diversity-Sensitive Conditional Generative Adversarial Networks
Comments Accepted as a conference paper at ICLR 2019
The Limitations of Adversarial Training and the Blind-Spot Attack
Comments Accepted by International Conference on Learning Representations (ICLR) 2019. Huan Zhang and Hongge Chen contributed equally
Learning Recurrent Binary/Ternary Weights
Comments Published as a conference paper at ICLR 2019
Augmented Cyclic Adversarial Learning for Low Resource Domain Adaptation
Comments 14 pages, 5 figures, 8 tables; Accepted as a conference paper at ICLR 2019
LayoutGAN: Generating Graphic Layouts with Wireframe Discriminators
Comments Accepted as a conference paper at ICLR 2019
