Papers
11,015 papers found
RGBD-GAN: Unsupervised 3D Representation Learning From Natural Image Datasets via RGBD Image Synthesis
Atsuhiro Noguchi, Tatsuya Harada
RIDE: Rewarding Impact-Driven Exploration for Procedurally-Generated Environments
Roberta Raileanu, Tim Rocktäschel
Ridge Regression: Structure, Cross-Validation, and Sketching
Sifan Liu, Edgar Dobriban
RNA Secondary Structure Prediction By Learning Unrolled Algorithms
Xinshi Chen, Yu Li, Ramzan Umarov et al.
RNNs Incrementally Evolving on an Equilibrium Manifold: A Panacea for Vanishing and Exploding Gradients?
Anil Kag, Ziming Zhang, Venkatesh Saligrama
Robust And Interpretable Blind Image Denoising Via Bias-Free Convolutional Neural Networks
Sreyas Mohan, Zahra Kadkhodaie, Eero P. Simoncelli et al.
Robust anomaly detection and backdoor attack detection via differential privacy
Min Du, Ruoxi Jia, Dawn Song
Robust Local Features for Improving the Generalization of Adversarial Training
Chuanbiao Song, Kun He, Jiadong Lin et al.
Robustness Verification for Transformers
Zhouxing Shi, Huan Zhang, Kai-Wei Chang et al.
Robust Reinforcement Learning for Continuous Control with Model Misspecification
Daniel J. Mankowitz, Nir Levine, Rae Jeong et al.
Robust Subspace Recovery Layer for Unsupervised Anomaly Detection
Chieh-Hsin Lai, Dongmian Zou, Gilad Lerman
Robust training with ensemble consensus
Jisoo Lee, Sae-Young Chung
Rotation-invariant clustering of neuronal responses in primary visual cortex
Ivan Ustyuzhaninov, Santiago A. Cadena, Emmanouil Froudarakis et al.
RTFM: Generalising to New Environment Dynamics via Reading
Victor Zhong, Tim Rocktäschel, Edward Grefenstette
SAdam: A Variant of Adam for Strongly Convex Functions
Guanghui Wang, Shiyin Lu, Quan Cheng et al.
Sample Efficient Policy Gradient Methods with Recursive Variance Reduction
Pan Xu, Felicia Gao, Quanquan Gu
Sampling-Free Learning of Bayesian Quantized Neural Networks
Jiahao Su, Milan Cvitkovic, Furong Huang
Scalable and Order-robust Continual Learning with Additive Parameter Decomposition
Jaehong Yoon, Saehoon Kim, Eunho Yang et al.
Scalable Model Compression by Entropy Penalized Reparameterization
Deniz Oktay, Johannes Ballé, Saurabh Singh et al.
Scalable Neural Methods for Reasoning With a Symbolic Knowledge Base
William W. Cohen, Haitian Sun, R. Alex Hofer et al.
Scale-Equivariant Steerable Networks
Ivan Sosnovik, Michał Szmaja, Arnold Smeulders
Scaling Autoregressive Video Models
Dirk Weissenborn, Oscar Täckström, Jakob Uszkoreit
SCALOR: Generative World Models with Scalable Object Representations
Jindong Jiang*, Sepehr Janghorbani*, Gerard De Melo et al.
SEED RL: Scalable and Efficient Deep-RL with Accelerated Central Inference
Lasse Espeholt, Raphaël Marinier, Piotr Stanczyk et al.
Selection via Proxy: Efficient Data Selection for Deep Learning
Cody Coleman, Christopher Yeh, Stephen Mussmann et al.