Papers
Autoencoder Image Interpolation by Shaping the Latent Space
Alon Oring, Zohar Yakhini, Yacov Hel-Or
Autoencoding Under Normalization Constraints
Sangwoong Yoon, Yung-Kyun Noh, Frank Park
Automatic variational inference with cascading flows
Luca Ambrogioni, Gianluigi Silvestri, Marcel van Gerven
Auto-NBA: Efficient and Effective Search Over the Joint Space of Networks, Bitwidths, and Accelerators
Yonggan Fu, Yongan Zhang, Yang Zhang et al.
Autoregressive Denoising Diffusion Models for Multivariate Probabilistic Time Series Forecasting
Kashif Rasul, Calvin Seward, Ingmar Schuster et al.
AutoSampling: Search for Effective Data Sampling Schedules
Ming Sun, Haoxuan Dou, Baopu Li et al.
A Value-Function-based Interior-point Method for Non-convex Bi-level Optimization
Risheng Liu, Xuan Liu, Xiaoming Yuan et al.
Average-Reward Off-Policy Policy Evaluation with Function Approximation
Shangtong Zhang, Yi Wan, Richard S Sutton et al.
A Wasserstein Minimax Framework for Mixed Linear Regression
Theo Diamandis, Yonina Eldar, Alireza Fallah et al.
A Zeroth-Order Block Coordinate Descent Algorithm for Huge-Scale Black-Box Optimization
Hanqin Cai, Yuchen Lou, Daniel Mckenzie et al.
Backdoor Scanning for Deep Neural Networks through K-Arm Optimization
Guangyu Shen, Yingqi Liu, Guanhong Tao et al.
Backpropagated Neighborhood Aggregation for Accurate Training of Spiking Neural Networks
Yukun Yang, Wenrui Zhang, Peng Li
BANG: Bridging Autoregressive and Non-autoregressive Generation with Large Scale Pretraining
Weizhen Qi, Yeyun Gong, Jian Jiao et al.
Barlow Twins: Self-Supervised Learning via Redundancy Reduction
Jure Zbontar, Li Jing, Ishan Misra et al.
BASE Layers: Simplifying Training of Large, Sparse Models
Mike Lewis, Shruti Bhosale, Tim Dettmers et al.
BASGD: Buffered Asynchronous SGD for Byzantine Learning
Yi-Rui Yang, Wu-Jun Li
Batch Value-function Approximation with Only Realizability
Tengyang Xie, Nan Jiang
Bayesian Algorithm Execution: Estimating Computable Properties of Black-box Functions Using Mutual Information
Willie Neiswanger, Ke Alexander Wang, Stefano Ermon
Bayesian Attention Belief Networks
Shujian Zhang, Xinjie Fan, Bo Chen et al.
Bayesian Deep Learning via Subnetwork Inference
Erik Daxberger, Eric Nalisnick, James U Allingham et al.
Bayesian Optimistic Optimisation with Exponentially Decaying Regret
Hung Tran-The, Sunil Gupta, Santu Rana et al.
Bayesian Optimization over Hybrid Spaces
Aryan Deshwal, Syrine Belakaria, Janardhan Rao Doppa
Bayesian Quadrature on Riemannian Data Manifolds
Christian Fröhlich, Alexandra Gessner, Philipp Hennig et al.
Bayesian Structural Adaptation for Continual Learning
Abhishek Kumar, Sunabha Chatterjee, Piyush Rai