Papers
11,955 papers found
Sampling-based inference for large linear models, with application to linearised Laplace
Javier Antoran, Shreyas Padhy, Riccardo Barbano et al.
Sampling-free Inference for Ab-Initio Potential Energy Surface Networks
Nicholas Gao, Stephan Günnemann
Sampling is as easy as learning the score: theory for diffusion models with minimal data assumptions
Sitan Chen, Sinho Chewi, Jerry Li et al.
Sampling with Mollified Interaction Energy Descent
Lingxiao Li, qiang liu, Anna Korba et al.
Satellite Navigation and Coordination with Limited Information Sharing
Sydney Dolan, Siddharth Nayak, Hamsa Balakrishnan
Scaffolding a Student to Instill Knowledge
Anil Kag, Durmus Alp Emre Acar, Aditya Gangrade et al.
Scalable and Equivariant Spherical CNNs by Discrete-Continuous (DISCO) Convolutions
Jeremy Ocampo, Matthew Alexander Price, Jason McEwen
Scalable Batch-Mode Deep Bayesian Active Learning via Equivalence Class Annealing
Renyu Zhang, Aly A Khan, Robert L. Grossman et al.
Scalable Subset Sampling with Neural Conditional Poisson Networks
Adeel Pervez, Phillip Lippe, Efstratios Gavves
Scaleformer: Iterative Multi-scale Refining Transformers for Time Series Forecasting
Mohammad Amin Shabani, Amir H. Abdi, Lili Meng et al.
Scale-invariant Bayesian Neural Networks with Connectivity Tangent Kernel
SungYub Kim, Sihwan Park, Kyung-Su Kim et al.
SCALE-UP: An Efficient Black-box Input-level Backdoor Detection via Analyzing Scaled Prediction Consistency
Junfeng Guo, Yiming Li, Xun Chen et al.
Scaling Forward Gradient With Local Losses
Mengye Ren, Simon Kornblith, Renjie Liao et al.
Scaling Laws for a Multi-Agent Reinforcement Learning Model
Oren Neumann, Claudius Gros
Scaling Laws For Deep Learning Based Image Reconstruction
Tobit Klug, Reinhard Heckel
Scaling Pareto-Efficient Decision Making via Offline Multi-Objective RL
Baiting Zhu, Meihua Dang, Aditya Grover
Scaling up and Stabilizing Differentiable Planning with Implicit Differentiation
Linfeng Zhao, Huazhe Xu, Lawson L.S. Wong
Scaling Up Probabilistic Circuits by Latent Variable Distillation
Anji Liu, Honghua Zhang, Guy Van den Broeck
Scenario-based Question Answering with Interacting Contextual Properties
Haitian Sun, William W. Cohen, Ruslan Salakhutdinov
Schema Inference for Interpretable Image Classification
Haofei Zhang, Mengqi Xue, Xiaokang Liu et al.
SCoMoE: Efficient Mixtures of Experts with Structured Communication
zhiyuan zeng, Deyi Xiong
Score-based Continuous-time Discrete Diffusion Models
Haoran Sun, Lijun Yu, Bo Dai et al.
SeaFormer: Squeeze-enhanced Axial Transformer for Mobile Semantic Segmentation
Qiang Wan, Zilong Huang, Jiachen Lu et al.
Searching Lottery Tickets in Graph Neural Networks: A Dual Perspective
Kun Wang, Yuxuan Liang, Pengkun Wang et al.
Seeing Differently, Acting Similarly: Heterogeneously Observable Imitation Learning
Xin-Qiang Cai, Yao-Xiang Ding, Zixuan Chen et al.