NeurIPS 2023: all accepted papers
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- Generalized Bayesian Inference for Scientific Simulators via Amortized Cost Estimation ↗Rui‐Bo Gao, Michael Deistler, Jakob H. Macke
- Generalized Belief Transport ↗Junqi Wang, Pei Wang, Patrick Shafto
- Generalized Weighted Path Consistency for Mastering Atari Games ↗Dengwei Zhao, Shikui Tu, Lei Xu
- Generalized equivalences between subsampling and ridge regularization ↗Pratik Patil, Jin‐Hong Du
- Generalized test utilities for long-tail performance in extreme multi-label classification ↗Erik Schultheis, Marek Wydmuch, Wojciech Kotłowski et al.
- Generating QM1B with PySCFIPU ↗Alexander Mathiasen, Hatem Helal, Kerstin Kläser et al.
- Generative Modelling of Stochastic Actions with Arbitrary Constraints in Reinforcement Learning ↗Changyu Chen, Ramesha Karunasena, Thành Luân Nguyễn et al.
- Generator Born from Classifier ↗Runpeng Yu, Xinchao Wang
- Generator Identification for Linear SDEs with Additive and Multiplicative Noise ↗Yuanyuan Wang, Xi Geng, Wei Huang et al.
- Geometric Analysis of Matrix Sensing over Graphs ↗Haixiang Zhang, Ying Chen, Javad Lavaei
- GloptiNets: Scalable Non-Convex Optimization with Certificates ↗Gaspard Beugnot, Julien Mairal, Alessandro Rudi
- GlucoSynth: Generating Differentially-Private Synthetic Glucose Traces ↗Josephine Lamp, Mark Derdzinski, Christopher Hannemann et al.
- Goal Driven Discovery of Distributional Differences via Language Descriptions ↗Ruiqi Zhong, Peter Zhang, Steve Li et al.
- Goal-conditioned Offline Planning from Curious Exploration ↗Marco Bagatella, Georg Martius
- Going Beyond Linear Mode Connectivity: The Layerwise Linear Feature Connectivity ↗Zhanpeng Zhou, Yongyi Yang, Xiaojiang Yang et al.
- Gradient-Based Feature Learning under Structured Data ↗Alireza Mousavi-Hosseini, Denny C.-Y. Wu, Taiji Suzuki et al.
- Graph-Structured Gaussian Processes for Transferable Graph Learning ↗Jun Wu, Lisa Ainsworth, Andrew D. B. Leakey et al.
- Grassmann Manifold Flows for Stable Shape Generation ↗Ryoma Yataka, Kazuki Hirashima, Masashi Shiraishi
- Grounding Neural Inference with Satisfiability Modulo Theories ↗Zifan Wang, Saranya Vijayakumar, Kaiji Lu et al.
- Guarantees for Self-Play in Multiplayer Games via Polymatrix Decomposability ↗Revan MacQueen, James R. Wright
- H-Consistency Bounds: Characterization and Extensions ↗Anqi Mao, Mehryar Mohri, Yutao Zhong
- H3T: Efficient Integration of Memory Optimization and Parallelism for Large-scale Transformer Training ↗Yuzhong Wang, Xu Han, Weilin Zhao et al.
- Hardness of Low Rank Approximation of Entrywise Transformed Matrix Products ↗Tamás Sarlós, Xingyou Song, David P. Woodruff et al.
- High-dimensional Contextual Bandit Problem without Sparsity ↗Junpei Komiyama, Masaaki Imaizumi
- History Filtering in Imperfect Information Games: Algorithms and Complexity ↗Christopher Solinas, Douglas Rebstock, Nathan Sturtevant et al.
- How do Minimum-Norm Shallow Denoisers Look in Function Space? ↗Chen Zeno, Greg Ongie, Yaniv Blumenfeld et al.
- How many samples are needed to leverage smoothness? ↗Vivien Cabannes, Stefano Vigogna
- How to Data in Datathons ↗Carlos Mougan, Richard R. Plant, Clare Teng et al.
- HubRouter: Learning Global Routing via Hub Generation and Pin-hub Connection ↗Xingbo Du, Chonghua Wang, Ruizhe Zhong et al.
- Hybrid Policy Optimization from Imperfect Demonstrations ↗Hanlin Yang, Chao Yu, Peng Sun et al.
- Hyper-HMM: aligning human brains and semantic features in a common latent event space ↗Caroline Lee, Jane Han, Ma Feilong et al.
- Hypothesis Selection with Memory Constraints ↗Maryam Aliakbarpour, Mark Bun, Adam Smith
- IDEA: An Invariant Perspective for Efficient Domain Adaptive Image Retrieval ↗Haixin Wang, Hao Wu, Jinan Sun et al.
- Ignorance is Bliss: Robust Control via Information Gating ↗Manan Tomar, Riashat Islam, Matthew Taylor et al.
- Im-Promptu: In-Context Composition from Image Prompts ↗Bhishma Dedhia, Michael Chang, Jake Snell et al.
- Imitation Learning from Vague Feedback ↗Xin-Qiang Cai, Yu-Jie Zhang, Chao-Kai Chiang et al.
- Implicit Contrastive Representation Learning with Guided Stop-gradient ↗Byeongchan Lee, SeHyun LEE
- Importance-aware Co-teaching for Offline Model-based Optimization ↗Ye Yuan, Can Chen, Zixuan Liu et al.
- Improved Algorithms for Stochastic Linear Bandits Using Tail Bounds for Martingale Mixtures ↗Hamish Flynn, David Reeb, Melih Kandemir et al.
- Improved Bayesian Regret Bounds for Thompson Sampling in Reinforcement Learning ↗Ahmadreza Moradipari, Mohammad Pedramfar, Modjtaba Shokrian Zini et al.
- Improvements on Uncertainty Quantification for Node Classification via Distance Based Regularization ↗Russell Hart, Linlin Yu, Yifei Lou et al.
- Improving the Knowledge Gradient Algorithm ↗Le Yang, Siyang Gao, Chin Pang Ho
- Incentivized Communication for Federated Bandits ↗Zhepei Wei, Chuanhao Li, Haifeng Xu et al.
- Information Maximizing Curriculum: A Curriculum-Based Approach for Learning Versatile Skills ↗Denis Blessing, Onur Celik, Xiaogang Jia et al.
- Information-guided Planning: An Online Approach for Partially Observable Problems ↗Matheus Aparecido Do Carmo Alves, Amokh Varma, Yehia Elkhatib et al.
- Initialization-Dependent Sample Complexity of Linear Predictors and Neural Networks ↗Roey Magen, Ohad Shamir
- Inner-Outer Aware Reconstruction Model for Monocular 3D Scene Reconstruction ↗Yu-Kun Qiu, Guo-Hao Xu, Wei-Shi Zheng
- Integration-free Training for Spatio-temporal Multimodal Covariate Deep Kernel Point Processes ↗Yixuan Zhang, Quyu Kong, Feng Zhou
- Interaction Measures, Partition Lattices and Kernel Tests for High-Order Interactions ↗Zhaolu Liu, Robert L. Peach, Pedro A. M. Mediano et al.
- Interpreting Unsupervised Anomaly Detection in Security via Rule Extraction ↗Ruoyu Li, Qing Li, Yu bao Zhang et al.
- Intervention Generalization: A View from Factor Graph Models ↗Gecia Bravo-Hermsdorff, David Watson, Jialin Yu et al.
- Invariant Anomaly Detection under Distribution Shifts: A Causal Perspective ↗João B. S. Carvalho, Mengtao Zhang, Robin Geyer et al.
- Is Learning in Games Good for the Learners? ↗William Brown, Jon Schneider, Kiran Vodrahalli
- Is This Loss Informative? Faster Text-to-Image Customization by Tracking Objective Dynamics ↗Anton Yu. Voronov, Mikhail Khoroshikh, Артем Вікторович Бабенко et al.
- Isometric Quotient Variational Auto-Encoders for Structure-Preserving Representation Learning ↗In Huh, Changwook Jeong, Jae Myung Choe et al.
- K-Nearest-Neighbor Local Sampling Based Conditional Independence Testing ↗Shuai Li, Yingjie Zhang, Hongtu Zhu et al.
- Katakomba: Tools and Benchmarks for Data-Driven NetHack ↗Vladislav Kurenkov, Alexander Nikulin, Denis Tarasov et al.
- Keep Various Trajectories: Promoting Exploration of Ensemble Policies in Continuous Control ↗Chao Li, Chen Gong, Qiang He et al.
- Kernel Quadrature with Randomly Pivoted Cholesky ↗Ethan N. Epperly, Elvira Moreno
- Kernel Stein Discrepancy thinning: a theoretical perspective of pathologies and a practical fix with regularization ↗Clément Bénard, Brian Staber, Sébastien da Veiga
- Kernel-Based Tests for Likelihood-Free Hypothesis Testing ↗Patrik Róbert Gerber, Tianze Jiang, Yury Polyanskiy et al.
- Kernelized Cumulants: Beyond Kernel Mean Embeddings ↗Patric Bonnier, Harald Oberhauser, Zoltán Szabó A
- Kissing to Find a Match: Efficient Low-Rank Permutation Representation ↗Hannah Dröge, Zorah Lähner, Yuval Bahat et al.
- Kullback-Leibler Maillard Sampling for Multi-armed Bandits with Bounded Rewards ↗Hao Qin, Kwang-Sung Jun, Chicheng Zhang
- LART: Neural Correspondence Learning with Latent Regularization Transformer for 3D Motion Transfer ↗Haoyu Chen, Hao Tang, Radu Timofte et al.
- LMC: Large Model Collaboration with Cross-assessment for Training-Free Open-Set Object Recognition ↗Haoxuan Qu, Xiaofei Hui, Yujun Cai et al.
- Label Correction of Crowdsourced Noisy Annotations with an Instance-Dependent Noise Transition Model ↗Hui Guo, Boyu Wang, Grace Yi
- LambdaBeam: Neural Program Search with Higher-Order Functions and Lambdas ↗Kensen Shi, Hanjun Dai, Wen-Ding Li et al.
- Large language models implicitly learn to straighten neural sentence trajectories to construct a predictive representation of natural language. ↗Eghbal A. Hosseini, Evelina G. Fedorenko
- Large language models transition from integrating across position-yoked, exponential windows to structure-yoked, power-law windows ↗David Skrill, Sam Norman-Haignere
- Large-Scale Distributed Learning via Private On-Device LSH ↗Tahseen Rabbani, Marco Bornstein, Furong Huang
- Latent Graph Inference with Limited Supervision ↗Jianglin Lu, Yi Xu, Huan Wang et al.
- Learning Adaptive Tensorial Density Fields for Clean Cryo-ET Reconstruction ↗Yuanhao Wang, Ramzi Idoughi, Heidrich Wolfgang
- Learning Adversarial Low-rank Markov Decision Processes with Unknown Transition and Full-information Feedback ↗Canzhe Zhao, Ruofeng Yang, Baoxiang Wang et al.
- Learning Curves for Noisy Heterogeneous Feature-Subsampled Ridge Ensembles ↗Ben R. Ruben, Cengiz Pehlevan
- Learning Dictionary for Visual Attention ↗Yingjie Liu, Xuan Liu, Hui Yu et al.
- Learning Efficient Surrogate Dynamic Models with Graph Spline Networks ↗Chuanbo Hua, Federico Berto, Michael Poli et al.
- Learning Exponential Families from Truncated Samples ↗Jane Lee, Andre Wibisono, Emmanouil Zampetakis
- Learning From Biased Soft Labels ↗Hua Yuan, Yu Shi, Ning Xu et al.
- Learning Interpretable Low-dimensional Representation via Physical Symmetry ↗Xuanjie Liu, Daniel Chin, Yichen Huang et al.
- Learning Invariant Representations with a Nonparametric Nadaraya-Watson Head ↗Alan Wang, Minh Quan Nguyen, Mert Rory Sabuncu
- Learning Large-Scale MTP2 Gaussian Graphical Models via Bridge-Block Decomposition ↗Xiwen Wang, Jiaxi Ying, Daniel P. Palomar
- Learning Large-scale Neural Fields via Context Pruned Meta-Learning ↗Jihoon Tack, Subin Kim, Sihyun Yu et al.
- Learning List-Level Domain-Invariant Representations for Ranking ↗Ruicheng Xian, Honglei Zhuang, Zhen Qin et al.
- Learning Modulated Transformation in GANs ↗Ceyuan Yang, Q. Zhang, Yinghao Xu et al.
- Learning Provably Robust Estimators for Inverse Problems via Jittering ↗Anselm Krainovic, Mahdi Soltanolkotabi, Reinhard Heckel
- Learning Rate Free Sampling in Constrained Domains ↗Louis Sharrock, Lester Mackey, Christopher Nemeth
- Learning Reliable Logical Rules with SATNet ↗Zhaoyu Li, Jinpei Guo, Yuhe Jiang et al.
- Learning Repeatable Speech Embeddings Using An Intra-class Correlation Regularizer ↗Jianwei Zhang, Suren Jayasuriya, Visar Berisha
- Learning Space-Time Continuous Latent Neural PDEs from Partially Observed States ↗Valerii Iakovlev, Markus Heinonen, Harri Lähdesmäki
- Learning Visual Prior via Generative Pre-Training ↗Jinheng Xie, Kai Ye, Yudong Li et al.
- Learning a 1-layer conditional generative model in total variation ↗Ajil Jalal, Justin Kang, Ananya Uppal et al.
- Learning a Neuron by a Shallow ReLU Network: Dynamics and Implicit Bias for Correlated Inputs ↗Dmitry Chistikov, Matthias Englert, Ranko Lazić
- Learning and processing the ordinal information of temporal sequences in recurrent neural circuits ↗Xiaolong Zou, Zhikun Chu, Qinghai Guo et al.
- Learning from Visual Observation via Offline Pretrained State-to-Go Transformer ↗Bohan Zhou, Ke Li, Jiechuan Jiang et al.
- Learning the Efficient Frontier ↗Philippe Chatigny, Ivan Sergienko, Ryan Ferguson et al.
- Lexinvariant Language Models ↗Qian Huang, Eric Zelikman, Sarah Chen et al.
- Limits, approximation and size transferability for GNNs on sparse graphs via graphops ↗Thien Le, Stefanie Jegelka
- Linear Time Algorithms for k-means with Multi-Swap Local Search ↗Junyu Huang, Qilong Feng, Ziyun Huang et al.
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