Papers
Rates of Estimation of Optimal Transport Maps using Plug-in Estimators via Barycentric Projections
NABARUN DEB, Promit Ghosal, Bodhisattva Sen
Raw Nav-merge Seismic Data to Subsurface Properties with MLP based Multi-Modal Information Unscrambler
Aditya Desai, Zhaozhuo Xu, Menal Gupta et al.
R-Drop: Regularized Dropout for Neural Networks
xiaobo liang, Lijun Wu, Juntao Li et al.
ReAct: Out-of-distribution Detection With Rectified Activations
Yiyou Sun, Chuan Guo, Yixuan Li
Realistic evaluation of transductive few-shot learning
Olivier Veilleux, Malik Boudiaf, Pablo Piantanida et al.
Rebooting ACGAN: Auxiliary Classifier GANs with Stable Training
Minguk Kang, Woohyeon Shim, Minsu Cho et al.
Rebounding Bandits for Modeling Satiation Effects
Liu Leqi, Fatma Kilinc Karzan, Zachary Lipton et al.
Recognizing Vector Graphics without Rasterization
XINYANG JIANG, LU LIU, Caihua Shan et al.
Reconstruction for Powerful Graph Representations
Leonardo Cotta, Christopher Morris, Bruno Ribeiro
Recovering Latent Causal Factor for Generalization to Distributional Shifts
Xinwei Sun, Botong Wu, Xiangyu Zheng et al.
Recovery Analysis for Plug-and-Play Priors using the Restricted Eigenvalue Condition
Jiaming Liu, Salman Asif, Brendt Wohlberg et al.
Rectangular Flows for Manifold Learning
Anthony L Caterini, Gabriel Loaiza-Ganem, Geoff Pleiss et al.
Rectifying the Shortcut Learning of Background for Few-Shot Learning
Xu Luo, Longhui Wei, Liangjian Wen et al.
Recurrence along Depth: Deep Convolutional Neural Networks with Recurrent Layer Aggregation
Jingyu Zhao, Yanwen Fang, Guodong Li
Recurrent Bayesian Classifier Chains for Exact Multi-Label Classification
Walter Gerych, Tom Hartvigsen, Luke Buquicchio et al.
Recurrent Submodular Welfare and Matroid Blocking Semi-Bandits
Orestis Papadigenopoulos, Constantine Caramanis
Recursive Bayesian Networks: Generalising and Unifying Probabilistic Context-Free Grammars and Dynamic Bayesian Networks
Robert Lieck, Martin Rohrmeier
Recursive Causal Structure Learning in the Presence of Latent Variables and Selection Bias
Sina Akbari, Ehsan Mokhtarian, AmirEmad Ghassami et al.
Redesigning the Transformer Architecture with Insights from Multi-particle Dynamical Systems
Subhabrata Dutta, Tanya Gautam, Soumen Chakrabarti et al.
RED : Looking for Redundancies for Data-FreeStructured Compression of Deep Neural Networks
Edouard YVINEC, Arnaud Dapogny, Matthieu Cord et al.
Reducing Collision Checking for Sampling-Based Motion Planning Using Graph Neural Networks
Chenning Yu, Sicun Gao
Reducing Information Bottleneck for Weakly Supervised Semantic Segmentation
Jungbeom Lee, Jooyoung Choi, Jisoo Mok et al.
Reducing the Covariate Shift by Mirror Samples in Cross Domain Alignment
Yin Zhao, minquan wang, Longjun Cai
Referring Transformer: A One-step Approach to Multi-task Visual Grounding
Muchen Li, Leonid Sigal