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title: "NeurIPS 2023 — all accepted papers, page 36 — Elamur Research"
description: "All 3,540 papers of NeurIPS 2023 · page 36 of 36, the most cited first; those with our summary link to it."
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# NeurIPS 2023: all accepted papers

3,540 papers · page 36 of 36 · the most cited first · [← NeurIPS 2023](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/2023/)

[← prev](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/2023/papers/page/35/) [1](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/2023/papers/) … [30](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/2023/papers/page/30/) … [35](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/2023/papers/page/35/) **36**

3501. **[Unbiased learning of deep generative models with structured discrete representations ↗](https://doi.org/10.52202/075280-3062)**Henry Bendekgey, Gabe Hope, Erik B. Sudderth
3502. **[Unbounded Differentially Private Quantile and Maximum Estimation ↗](https://doi.org/10.52202/075280-3394)**David Durfee
3503. **[Unconstrained Dynamic Regret via Sparse Coding ↗](https://doi.org/10.52202/075280-3263)**Zhiyu Zhang, Ashok Cutkosky, Yannis Paschalidis
3504. **[Uncoupled and Convergent Learning in Two-Player Zero-Sum Markov Games with Bandit Feedback ↗](https://doi.org/10.52202/075280-1579)**Yang Cai, Haipeng Luo, Chen-Yu Wei et al.
3505. **[Uncovering Meanings of Embeddings via Partial Orthogonality ↗](https://doi.org/10.52202/075280-1388)**Yibo Jiang, Bryon Aragam, Victor Veitch
3506. **[Undirected Probabilistic Model for Tensor Decomposition ↗](https://doi.org/10.52202/075280-1124)**Zerui Tao, Toshihisa Tanaka, Qibin Zhao
3507. **[UniT: A Unified Look at Certified Robust Training against Text Adversarial Perturbation ↗](https://doi.org/10.52202/075280-0981)**Muchao Ye, Ziyi Yin, Tianrong Zhang et al.
3508. **[Uniform Convergence with Square-Root Lipschitz Loss ↗](https://doi.org/10.52202/075280-0570)**Lijia Zhou, Zhen Dai, Frederic Koehler et al.
3509. **[Unifying Predictions of Deterministic and Stochastic Physics in Mesh-reduced Space with Sequential Flow Generative Model ↗](https://doi.org/10.52202/075280-2648)**Luning Sun, Xu Han, Han Gao et al.
3510. **[Universal Online Learning with Gradient Variations: A Multi-layer Online Ensemble Approach ↗](https://doi.org/10.52202/075280-1639)**Yu-Hu Yan, Peng Zhao, Zhi-Hua Zhou
3511. **[Universality laws for Gaussian mixtures in generalized linear models ↗](https://doi.org/10.52202/075280-2388)**Yatin Dandi, Ludovic Stephan, Florent Krząkała et al.
3512. **[Unlocking Deterministic Robustness Certification on ImageNet ↗](https://doi.org/10.52202/075280-1863)**Kai Hu, Andy Zou, Zifan Wang et al.
3513. **[Unsupervised Behavior Extraction via Random Intent Priors ↗](https://doi.org/10.52202/075280-2242)**Hao Hu, Yiqin Yang, Jianing Ye et al.
3514. **[V-InFoR: A Robust Graph Neural Networks Explainer for Structurally Corrupted Graphs ↗](https://doi.org/10.52202/075280-2464)**Senzhang Wang, Jun Yin, Chaozhuo Li et al.
3515. **[VTaC: A Benchmark Dataset of Ventricular Tachycardia Alarms from ICU Monitors ↗](https://doi.org/10.52202/075280-1686)**Li-wei H. Lehman, Benjamin Moody, Harsh Deep et al.
3516. **[VaRT: Variational Regression Trees ↗](https://doi.org/10.52202/075280-1979)**Sebastian Salazar
3517. **[Variational Gaussian Processes with Decoupled Conditionals ↗](https://doi.org/10.52202/075280-2003)**Xinran Zhu, Kaiwen Wu, Natalie Maus et al.
3518. **[Variational Weighting for Kernel Density Ratios ↗](https://doi.org/10.52202/075280-0222)**Sangwoong Yoon, Frank C. Park, Gunsu Yun et al.
3519. **[Versatile Energy-Based Probabilistic Models for High Energy Physics ↗](https://doi.org/10.52202/075280-0845)**Taoli Cheng, Aaron C. Courville
3520. **[ViSt3D: Video Stylization with 3D CNN ↗](https://doi.org/10.52202/075280-1803)**Ayush Pande, Gaurav Sharma
3521. **[Video Timeline Modeling For News Story Understanding ↗](https://doi.org/10.52202/075280-1230)**Meng Liu, Mingda Zhang, Jialu Liu et al.
3522. **[VisAlign: Dataset for Measuring the Alignment between AI and Humans in Visual Perception ↗](https://doi.org/10.52202/075280-3373)**Jiyoung Lee, Seungho Kim, Seunghyun Won et al.
3523. **[WCLD: Curated Large Dataset of Criminal Cases from Wisconsin Circuit Courts ↗](https://doi.org/10.52202/075280-0554)**Elliott Ash, Naman Goel, Nianyun Li et al.
3524. **[WalkLM: A Uniform Language Model Fine-tuning Framework for Attributed Graph Embedding ↗](https://doi.org/10.52202/075280-0584)**Yanchao Tan, Zihao Zhou, Hang Lv et al.
3525. **[Wasserstein Gradient Flows for Optimizing Gaussian Mixture Policies ↗](https://doi.org/10.52202/075280-0921)**Hanna Ziesche, Leonel Dario Rozo
3526. **[Weighted ROC Curve in Cost Space: Extending AUC to Cost-Sensitive Learning ↗](https://doi.org/10.52202/075280-0760)**Huiyang Shao, Qianqian Xu, Zhiyong Yang et al.
3527. **[Weitzman's Rule for Pandora's Box with Correlations ↗](https://doi.org/10.52202/075280-0555)**Evangelia Gergatsouli, Christos Tzamos
3528. **[What Distributions are Robust to Indiscriminate Poisoning Attacks for Linear Learners? ↗](https://doi.org/10.52202/075280-1519)**Fnu Suya, Xiao Zhang, Yuan Tian et al.
3529. **[What Makes Data Suitable for a Locally Connected Neural Network? A Necessary and Sufficient Condition Based on Quantum Entanglement. ↗](https://doi.org/10.52202/075280-1785)**Yotam Alexander, Nimrod De La Vega, Noam Razin et al.
3530. **[What Planning Problems Can A Relational Neural Network Solve? ↗](https://doi.org/10.52202/075280-2601)**Jiayuan Mao, Tomás Lozano‐Pérez, Joshua B. Tenenbaum et al.
3531. **[What is Flagged in Uncertainty Quantification? Latent Density Models for Uncertainty Categorization ↗](https://doi.org/10.52202/075280-0208)**Hao Sun, Boris van Breugel, Jonathan Crabbé et al.
3532. **[What is the Inductive Bias of Flatness Regularization? A Study of Deep Matrix Factorization Models ↗](https://doi.org/10.52202/075280-1217)**Khashayar Gatmiry, Zhiyuan Li, Tengyu Ma et al.
3533. **[When Can We Track Significant Preference Shifts in Dueling Bandits? ↗](https://doi.org/10.52202/075280-1666)**Joe Suk, Arpit Agarwal
3534. **[When can Regression-Adjusted Control Variate Help? Rare Events, Sobolev Embedding and Minimax Optimality ↗](https://doi.org/10.52202/075280-1589)**José Blanchet, Haoxuan Chen, Yiping Lu et al.
3535. **[When is Agnostic Reinforcement Learning Statistically Tractable? ↗](https://doi.org/10.52202/075280-1209)**Zeyu Jia, Gene Li, Alexander Rakhlin et al.
3536. **[Wyze Rule: Federated Rule Dataset for Rule Recommendation Benchmarking ↗](https://doi.org/10.52202/075280-0044)**Mohammad Mahdi Kamani, Yuhang Yao, Hanjia Lyu et al.
3537. **[Zero-One Laws of Graph Neural Networks ↗](https://doi.org/10.52202/075280-3099)**Sam Adam-Day, Iliant Iliant, Ismail Ceylan
3538. **[p-value Adjustment for Monotonous, Unbiased, and Fast Clustering Comparison ↗](https://doi.org/10.52202/075280-1180)**Kai Klede, Thomas Altstidl, Dario Zanca et al.
3539. **[ε-fractional core stability in Hedonic Games. ↗](https://doi.org/10.52202/075280-1249)**Simone Fioravanti, Michele Flammini, Bojana Kodric et al.
3540. **[“Why Not Looking backward?” A Robust Two-Step Method to Automatically Terminate Bayesian Optimization ↗](https://doi.org/10.52202/075280-1881)**Shuang Li, Ke Li, Wei Li

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