Papers
Learning Theory Can (Sometimes) Explain Generalisation in Graph Neural Networks
Pascal Esser, Leena Chennuru Vankadara, Debarghya Ghoshdastidar
Learning to Adapt via Latent Domains for Adaptive Semantic Segmentation
Yunan Liu, Shanshan Zhang, Yang Li et al.
Learning to Assimilate in Chaotic Dynamical Systems
Michael McCabe, Jed Brown
Learning to Combine Per-Example Solutions for Neural Program Synthesis
Disha Shrivastava, Hugo Larochelle, Daniel Tarlow
Learning to Compose Visual Relations
Nan Liu, Shuang Li, Yilun Du et al.
Learning to dehaze with polarization
Chu Zhou, Minggui Teng, Yufei Han et al.
Learning to delegate for large-scale vehicle routing
Sirui Li, Zhongxia Yan, Cathy Wu
Learning to Draw: Emergent Communication through Sketching
Daniela Mihai, Jonathon Hare
Learning to Elect
Cem Anil, Xuchan Bao
Learning to Execute: Efficient Learning of Universal Plan-Conditioned Policies in Robotics
Ingmar Schubert, Danny Driess, Ozgur S. Oguz et al.
Learning to Generate Realistic Noisy Images via Pixel-level Noise-aware Adversarial Training
Yuanhao Cai, Xiaowan Hu, Haoqian Wang et al.
Learning to Generate Visual Questions with Noisy Supervision
Shen Kai, Lingfei Wu, Siliang Tang et al.
Learning to Ground Multi-Agent Communication with Autoencoders
Toru Lin, Jacob Huh, Christopher Stauffer et al.
Learning to Iteratively Solve Routing Problems with Dual-Aspect Collaborative Transformer
Yining Ma, Jingwen Li, Zhiguang Cao et al.
Learning to Learn Dense Gaussian Processes for Few-Shot Learning
Ze Wang, Zichen Miao, Xiantong Zhen et al.
Learning to Learn Graph Topologies
Xingyue Pu, Tianyue Cao, Xiaoyun Zhang et al.
Learning-to-learn non-convex piecewise-Lipschitz functions
Maria-Florina F Balcan, Mikhail Khodak, Dravyansh Sharma et al.
Learning to Predict Trustworthiness with Steep Slope Loss
Yan Luo, Yongkang Wong, Mohan S Kankanhalli et al.
Learning to Schedule Heuristics in Branch and Bound
Antonia Chmiela, Elias Khalil, Ambros Gleixner et al.
Learning to See by Looking at Noise
Manel Baradad Jurjo, Jonas Wulff, Tongzhou Wang et al.
Learning to Select Exogenous Events for Marked Temporal Point Process
Ping Zhang, Rishabh Iyer, Ashish Tendulkar et al.
Learning to Simulate Self-driven Particles System with Coordinated Policy Optimization
Zhenghao Peng, Quanyi Li, Ka Ming Hui et al.
Learning to Synthesize Programs as Interpretable and Generalizable Policies
Dweep Trivedi, Jesse Zhang, Shao-Hua Sun et al.
Learning to Time-Decode in Spiking Neural Networks Through the Information Bottleneck
Nicolas Skatchkovsky, Osvaldo Simeone, Hyeryung Jang
Learning Transferable Adversarial Perturbations
Krishna kanth Nakka, Mathieu Salzmann