Papers
A Continuous Mapping For Augmentation Design
Keyu Tian, Chen Lin, Ser Nam Lim et al.
A Contrastive Learning Approach for Training Variational Autoencoder Priors
Jyoti Aneja, Alex Schwing, Jan Kautz et al.
A Convergence Analysis of Gradient Descent on Graph Neural Networks
Pranjal Awasthi, Abhimanyu Das, Sreenivas Gollapudi
A Critical Look at the Consistency of Causal Estimation with Deep Latent Variable Models
Severi Rissanen, Pekka Marttinen
Across-animal odor decoding by probabilistic manifold alignment
Pedro Herrero-Vidal, Dmitry Rinberg, Cristina Savin
Action-guided 3D Human Motion Prediction
Jiangxin Sun, Zihang Lin, Xintong Han et al.
Activation Sharing with Asymmetric Paths Solves Weight Transport Problem without Bidirectional Connection
Sunghyeon Woo, Jeongwoo Park, Jiwoo Hong et al.
Active 3D Shape Reconstruction from Vision and Touch
Edward Smith, David Meger, Luis Pineda et al.
Active Assessment of Prediction Services as Accuracy Surface Over Attribute Combinations
Vihari Piratla, Soumen Chakrabarti, Sunita Sarawagi
Active clustering for labeling training data
Quentin Lutz, Elie de Panafieu, Maya Stein et al.
Active Learning of Convex Halfspaces on Graphs
Maximilian Thiessen, Thomas Gaertner
Actively Identifying Causal Effects with Latent Variables Given Only Response Variable Observable
Tian-Zuo Wang, Zhi-Hua Zhou
Active Offline Policy Selection
Ksenia Konyushova, Yutian Chen, Thomas Paine et al.
Adaptable Agent Populations via a Generative Model of Policies
Kenneth Derek, Phillip Isola
Adapting to function difficulty and growth conditions in private optimization
Hilal Asi, Daniel Levy, John C. Duchi
Adaptive Conformal Inference Under Distribution Shift
Isaac Gibbs, Emmanuel Candes
Adaptive Data Augmentation on Temporal Graphs
Yiwei Wang, Yujun Cai, Yuxuan Liang et al.
Adaptive Denoising via GainTuning
Sreyas Mohan, Joshua L Vincent, Ramon Manzorro et al.
Adaptive Diffusion in Graph Neural Networks
Jialin Zhao, Yuxiao Dong, Ming Ding et al.
Adaptive Ensemble Q-learning: Minimizing Estimation Bias via Error Feedback
Hang Wang, Sen Lin, Junshan Zhang
Adaptive First-Order Methods Revisited: Convex Minimization without Lipschitz Requirements
Kimon Antonakopoulos, Panayotis Mertikopoulos
Adaptive Machine Unlearning
Varun Gupta, Christopher Jung, Seth Neel et al.
Adaptive Online Packing-guided Search for POMDPs
Chenyang Wu, Guoyu Yang, Zongzhang Zhang et al.
Adaptive Proximal Gradient Methods for Structured Neural Networks
Jihun Yun, Aurelie C. Lozano, Eunho Yang
Adaptive Risk Minimization: Learning to Adapt to Domain Shift
Marvin Zhang, Henrik Marklund, Nikita Dhawan et al.