Papers
Black-Box Ripper: Copying black-box models using generative evolutionary algorithms
Antonio Barbalau, Adrian Cosma, Radu Tudor Ionescu et al.
Blind Video Temporal Consistency via Deep Video Prior
Chenyang Lei, Yazhou Xing, Qifeng Chen
BlockGAN: Learning 3D Object-aware Scene Representations from Unlabelled Images
Thu H Nguyen-Phuoc, Christian Richardt, Long Mai et al.
Bongard-LOGO: A New Benchmark for Human-Level Concept Learning and Reasoning
Weili Nie, Zhiding Yu, Lei Mao et al.
Boosting Adversarial Training with Hypersphere Embedding
Tianyu Pang, Xiao Yang, Yinpeng Dong et al.
Boosting First-Order Methods by Shifting Objective: New Schemes with Faster Worst-Case Rates
Kaiwen Zhou, Anthony Man-Cho So, James Cheng
Bootstrapping neural processes
Juho Lee, Yoonho Lee, Jungtaek Kim et al.
Bootstrap Your Own Latent - A New Approach to Self-Supervised Learning
Jean-Bastien Grill, Florian Strub, Florent Altché et al.
BOSS: Bayesian Optimization over String Spaces
Henry Moss, David Leslie, Daniel Beck et al.
BoTorch: A Framework for Efficient Monte-Carlo Bayesian Optimization
Maximilian Balandat, Brian Karrer, Daniel Jiang et al.
Boundary thickness and robustness in learning models
Yaoqing Yang, Rajiv Khanna, Yaodong Yu et al.
BoxE: A Box Embedding Model for Knowledge Base Completion
Ralph Abboud, Ismail Ceylan, Thomas Lukasiewicz et al.
Breaking Reversibility Accelerates Langevin Dynamics for Non-Convex Optimization
Xuefeng GAO, Mert Gurbuzbalaban, Lingjiong Zhu
Breaking the Communication-Privacy-Accuracy Trilemma
Wei-Ning Chen, Peter Kairouz, Ayfer Ozgur
Breaking the Sample Size Barrier in Model-Based Reinforcement Learning with a Generative Model
Gen Li, Yuting Wei, Yuejie Chi et al.
Bridging Imagination and Reality for Model-Based Deep Reinforcement Learning
Guangxiang Zhu, Minghao Zhang, Honglak Lee et al.
Bridging the Gap between Sample-based and One-shot Neural Architecture Search with BONAS
Han Shi, Renjie Pi, Hang Xu et al.
BRP-NAS: Prediction-based NAS using GCNs
Lukasz Dudziak, Thomas Chau, Mohamed Abdelfattah et al.
Building powerful and equivariant graph neural networks with structural message-passing
Clément Vignac, Andreas Loukas, Pascal Frossard
Byzantine Resilient Distributed Multi-Task Learning
Jiani Li, Waseem Abbas, Xenofon Koutsoukos
Calibrated Reliable Regression using Maximum Mean Discrepancy
Peng Cui, Wenbo Hu, Jun Zhu
Calibrating CNNs for Lifelong Learning
Pravendra Singh, Vinay Kumar Verma, Pratik Mazumder et al.
Calibrating Deep Neural Networks using Focal Loss
Jishnu Mukhoti, Viveka Kulharia, Amartya Sanyal et al.
Calibration of Shared Equilibria in General Sum Partially Observable Markov Games
Nelson Vadori, Sumitra Ganesh, Prashant Reddy et al.
Can Graph Neural Networks Count Substructures?
Zhengdao Chen, Lei Chen, Soledad Villar et al.