Papers
Scalable Thompson Sampling using Sparse Gaussian Process Models
Sattar Vakili, Henry Moss, Artem Artemev et al.
Scalars are universal: Equivariant machine learning, structured like classical physics
Soledad Villar, David W Hogg, Kate Storey-Fisher et al.
ScaleCert: Scalable Certified Defense against Adversarial Patches with Sparse Superficial Layers
Husheng Han, Kaidi Xu, Xing Hu et al.
Scaling Ensemble Distribution Distillation to Many Classes with Proxy Targets
Max Ryabinin, Andrey Malinin, Mark Gales
Scaling Gaussian Processes with Derivative Information Using Variational Inference
Misha Padidar, Xinran Zhu, Leo Huang et al.
Scaling Neural Tangent Kernels via Sketching and Random Features
Amir Zandieh, Insu Han, Haim Avron et al.
Scaling up Continuous-Time Markov Chains Helps Resolve Underspecification
Alkis Gotovos, Rebekka Burkholz, John Quackenbush et al.
Scaling Up Exact Neural Network Compression by ReLU Stability
Thiago Serra, Xin Yu, Abhinav Kumar et al.
Scaling Vision with Sparse Mixture of Experts
Carlos Riquelme, Joan Puigcerver, Basil Mustafa et al.
Scallop: From Probabilistic Deductive Databases to Scalable Differentiable Reasoning
Jiani Huang, Ziyang Li, Binghong Chen et al.
Scatterbrain: Unifying Sparse and Low-rank Attention
Beidi Chen, Tri Dao, Eric Winsor et al.
Scheduling jobs with stochastic holding costs
Dabeen Lee, Milan Vojnovic
Score-based Generative Modeling in Latent Space
Arash Vahdat, Karsten Kreis, Jan Kautz
Score-based Generative Neural Networks for Large-Scale Optimal Transport
Mara Daniels, Tyler Maunu, Paul Hand
SE(3)-equivariant prediction of molecular wavefunctions and electronic densities
Oliver Unke, Mihail Bogojeski, Michael Gastegger et al.
SEAL: Self-supervised Embodied Active Learning using Exploration and 3D Consistency
Devendra Singh Chaplot, Murtaza Dalal, Saurabh Gupta et al.
Searching for Efficient Transformers for Language Modeling
David So, Wojciech Mańke, Hanxiao Liu et al.
Searching Parameterized AP Loss for Object Detection
Tao Chenxin, Zizhang Li, Xizhou Zhu et al.
Searching the Search Space of Vision Transformer
Minghao Chen, Kan Wu, Bolin Ni et al.
Second-Order Neural ODE Optimizer
Guan-Horng Liu, Tianrong Chen, Evangelos Theodorou
See More for Scene: Pairwise Consistency Learning for Scene Classification
Gongwei Chen, Xinhang Song, Bohan Wang et al.
SegFormer: Simple and Efficient Design for Semantic Segmentation with Transformers
Enze Xie, Wenhai Wang, Zhiding Yu et al.
Selective Sampling for Online Best-arm Identification
Romain Camilleri, Zhihan Xiong, Maryam Fazel et al.
Self-Adaptable Point Processes with Nonparametric Time Decays
Zhimeng Pan, Zheng Wang, Jeff M Phillips et al.
Self-Attention Between Datapoints: Going Beyond Individual Input-Output Pairs in Deep Learning
Jannik Kossen, Neil Band, Clare Lyle et al.