Poster Papers
24,624 papers found • Page 455 of 493
Conference
SAMFusion: Sensor-Adaptive Multimodal Fusion for 3D Object Detection in Adverse Weather
Edoardo Palladin, Roland Dietze, Praveen Narayanan et al.
SAM-guided Graph Cut for 3D Instance Segmentation
Haoyu Guo, He Zhu, Sida Peng et al.
Sample as you Infer: Predictive Coding with Langevin Dynamics
Umais Zahid, Qinghai Guo, Zafeirios Fountas
Sample Average Approximation for Conditional Stochastic Optimization with Dependent Data
Yafei Wang, Bo Pan, Mei Li et al.
Sample Complexity Bounds for Estimating Probability Divergences under Invariances
Behrooz Tahmasebi, Stefanie Jegelka
Sample-Efficiency in Multi-Batch Reinforcement Learning: The Need for Dimension-Dependent Adaptivity
Emmeran Johnson, Ciara Pike-Burke, Patrick Rebeschini
Sample-efficient Learning of Infinite-horizon Average-reward MDPs with General Function Approximation
Jianliang He, Han Zhong, Zhuoran Yang
Sample-Efficient Learning of POMDPs with Multiple Observations In Hindsight
Jiacheng Guo, Minshuo Chen, Huan Wang et al.
Sample-Efficient Multiagent Reinforcement Learning with Reset Replay
Yaodong Yang, Guangyong Chen, Jianye Hao et al.
Sample-Efficient Multi-Agent RL: An Optimization Perspective
Nuoya Xiong, Zhihan Liu, Zhaoran Wang et al.
Sample Efficient Myopic Exploration Through Multitask Reinforcement Learning with Diverse Tasks
Ziping Xu, Zifan Xu, Runxuan Jiang et al.
Sample-Efficient Robust Multi-Agent Reinforcement Learning in the Face of Environmental Uncertainty
Laixi Shi, Eric Mazumdar, Yuejie Chi et al.
Sampling-based Multi-dimensional Recalibration
Youngseog Chung, Ian Char, Jeff Schneider
Sampling in Unit Time with Kernel Fisher-Rao Flow
Aimee Maurais, Youssef Marzouk
Sampling is as easy as keeping the consistency: convergence guarantee for Consistency Models
Junlong Lyu, Zhitang Chen, Shoubo Feng
Sampling Multimodal Distributions with the Vanilla Score: Benefits of Data-Based Initialization
Frederic Koehler, Thuy-Duong Vuong
SANeRF-HQ: Segment Anything for NeRF in High Quality
Yichen Liu, Benran Hu, Chi-Keung Tang et al.
SAN: Inducing Metrizability of GAN with Discriminative Normalized Linear Layer
Yuhta Takida, Masaaki Imaizumi, Takashi Shibuya et al.
SAOR: Single-View Articulated Object Reconstruction
Mehmet Aygun, Oisin Mac Aodha
SAPG: Split and Aggregate Policy Gradients
Jayesh Singla, Ananye Agarwal, Deepak Pathak
Sapiens: Foundation for Human Vision Models
Rawal Khirodkar, Timur Bagautdinov, Julieta Martinez et al.
Sarah Frank-Wolfe: Methods for Constrained Optimization with Best Rates and Practical Features
Aleksandr Beznosikov, David Dobre, Gauthier Gidel
SAS: Structured Activation Sparsification
Yusuke Sekikawa, Shingo Yashima
SatSynth: Augmenting Image-Mask Pairs through Diffusion Models for Aerial Semantic Segmentation
Aysim Toker, Marvin Eisenberger, Daniel Cremers et al.
SAVE: Protagonist Diversification with Structure Agnostic Video Editing
Yeji Song, Wonsik Shin, Junsoo Lee et al.
SaVeR: Optimal Data Collection Strategy for Safe Policy Evaluation in Tabular MDP
Subhojyoti Mukherjee, Josiah Hanna, Robert Nowak
SC4D: Sparse-Controlled Video-to-4D Generation and Motion Transfer
Zijie Wu, Chaohui Yu, Yanqin Jiang et al.
Scalable 3D Registration via Truncated Entry-wise Absolute Residuals
Tianyu Huang, Liangzu Peng, Rene Vidal et al.
Scalable AI Safety via Doubly-Efficient Debate
Jonah Brown-Cohen, Geoffrey Irving, Georgios Piliouras
Scalable and Effective Implicit Graph Neural Networks on Large Graphs
Juncheng Liu, Bryan Hooi, Kenji Kawaguchi et al.
Scalable and Flexible Causal Discovery with an Efficient Test for Adjacency
Alan Amin, Andrew Wilson
Scalable Diffusion for Materials Generation
Sherry Yang, Kwanghwan Cho, Amil Merchant et al.
Scalable Group Choreography via Variational Phase Manifold Learning
Nhat Le, Khoa Do, Xuan Bui et al.
Scalable High-Resolution Pixel-Space Image Synthesis with Hourglass Diffusion Transformers
Katherine Crowson, Stefan Baumann, Alex Birch et al.
Scalable Language Model with Generalized Continual Learning
Bohao PENG, Zhuotao Tian, Shu Liu et al.
Scalable Modular Network: A Framework for Adaptive Learning via Agreement Routing
Minyang Hu, Hong Chang, Bingpeng Ma et al.
Scalable Monotonic Neural Networks
Hyunho Kim, Jong-Seok Lee
Scalable Multiple Kernel Clustering: Learning Clustering Structure from Expectation
Weixuan Liang, En Zhu, Shengju Yu et al.
Scalable Neural Network Kernels
Arijit Sehanobish, Krzysztof Choromanski, YUNFAN ZHAO et al.
Scalable Online Exploration via Coverability
Philip Amortila, Dylan Foster, Akshay Krishnamurthy
Scalable Pre-training of Large Autoregressive Image Models
Alaaeldin Ali, Michal Klein, Shuangfei Zhai et al.
Scalable Real-Time Recurrent Learning Using Columnar-Constructive Networks
Khurram Javed, Haseeb Shah, Richard Sutton et al.
Scalable Real-Time Recurrent Learning Using Columnar-Constructive Networks
Khurram Javed, Haseeb Shah, Richard Sutton et al.
Scalable Safe Policy Improvement for Factored Multi-Agent MDPs
Federico Bianchi, Edoardo Zorzi, Alberto Castellini et al.
Scalable Wasserstein Gradient Flow for Generative Modeling through Unbalanced Optimal Transport
Jaemoo Choi, Jaewoong Choi, Myungjoo Kang
Scalar Function Topology Divergence: Comparing Topology of 3D Objects
Ilya Trofimov, Daria Voronkova, Eduard Tulchinskii et al.
Scale-Adaptive Diffusion Model for Complex Sketch Synthesis
Jijin Hu, Ke Li, Yonggang Qi et al.
Scaled Decoupled Distillation
Shicai Wei, Chunbo Luo, Yang Luo
ScaleDreamer: Scalable Text-to-3D Synthesis with Asynchronous Score Distillation
Zhiyuan MA, Yuxiang WEI, Yabin Zhang et al.
Scale-Free Image Keypoints Using Differentiable Persistent Homology
Giovanni Barbarani, Francesco Vaccarino, Gabriele Trivigno et al.