NEURIPS Papers
5,858 papers found • Page 19 of 118
Conditional Distribution Compression via the Kernel Conditional Mean Embedding
Dominic Broadbent, Nick Whiteley, Robert Allison et al.
Conditional Forecasts and Proper Scoring Rules for Reliable and Accurate Performative Predictions
Philip Boeken, Onno Zoeter, Joris Mooij
Conditional Gradient Methods with Standard LMO for Stochastic Simple Bilevel Optimization
Khanh-Hung (Bruce) Giang-Tran, Soroosh Shafiee, Nam Ho-Nguyen
Conditional Panoramic Image Generation via Masked Autoregressive Modeling
Chaoyang Wang, Xiangtai Li, Lu Qi et al.
Conditional Representation Learning for Customized Tasks
Honglin Liu, Chao Sun, Peng Hu et al.
Conditioning Matters: Training Diffusion Policies is Faster Than You Think
Zibin Dong, Yicheng Liu, Yinchuan Li et al.
Confidence-Aware With Prototype Alignment for Partial Multi-label Learning
Weijun Lv, Yu Chen, Xiaozhao Fang et al.
Conflict-Aware Knowledge Editing in the Wild: Semantic-Augmented Graph Representation for Unstructured Text
Zhange Zhang, Zhicheng Geng, Yuqing Ma et al.
Conformal Arbitrage: Risk-Controlled Balancing of Competing Objectives in Language Models
William Overman, Mohsen Bayati
Conformal Inference under High-Dimensional Covariate Shifts via Likelihood-Ratio Regularization
Sunay Joshi, Shayan Kiyani, George J. Pappas et al.
Conformal Information Pursuit for Interactively Guiding Large Language Models
Kwan Ho Ryan Chan, Yuyan Ge, Edgar Dobriban et al.
Conformal Linguistic Calibration: Trading-off between Factuality and Specificity
Zhengping Jiang, Anqi Liu, Ben Van Durme
Conformal Mixed-Integer Constraint Learning with Feasibility Guarantees
Daniel Ovalle, Lorenz Biegler, Ignacio Grossmann et al.
Conformal Online Learning of Deep Koopman Linear Embeddings
Ben Gao, Jordan Patracone, Stephane Chretien et al.
Conformal Prediction Beyond the Horizon: Distribution-Free Inference for Policy Evaluation
Feichen Gan, Lu Youcun, Yingying Zhang et al.
Conformal Prediction Beyond the Seen: A Missing Mass Perspective for Uncertainty Quantification in Generative Models
Sima Noorani, Shayan Kiyani, George J. Pappas et al.
Conformal Prediction for Causal Effects of Continuous Treatments
Maresa Schröder, Dennis Frauen, Jonas Schweisthal et al.
Conformal Prediction for Ensembles: Improving Efficiency via Score-Based Aggregation
Yash Patel, Eduardo Ochoa Rivera, Ambuj Tewari
Conformal Prediction for Time-series Forecasting with Change Points
Sophia Sun, Rose Yu
Conformal Prediction in The Loop: A Feedback-Based Uncertainty Model for Trajectory Optimization
Han Wang, Chao Ning
Conformal Prediction under Lévy-Prokhorov Distribution Shifts: Robustness to Local and Global Perturbations
Liviu Aolaritei, Julie Zhu, Oliver Wang et al.
Conformal Risk Training: End-to-End Optimization of Conformal Risk Control
Christopher Yeh, Nicolas Christianson, Adam Wierman et al.
Confounding Robust Deep Reinforcement Learning: A Causal Approach
Mingxuan Li, Junzhe Zhang, Elias Bareinboim
ConfTuner: Training Large Language Models to Express Their Confidence Verbally
Yibo Li, Miao Xiong, Jiaying Wu et al.
Confusion-Driven Self-Supervised Progressively Weighted Ensemble Learning for Non-Exemplar Class Incremental Learning
Kai Hu, Zhang Yu, Yuan Zhang et al.
Connecting Jensen–Shannon and Kullback–Leibler Divergences: A New Bound for Representation Learning
Reuben Dorent, Polina Golland, William (Sandy) Wells
Connecting Neural Models Latent Geometries with Relative Geodesic Representations
Hanlin Yu, Berfin Inal, Georgios Arvanitidis et al.
Connectome-Based Modelling Reveals Orientation Maps in the Drosophila Optic Lobe
Jia Nuo Liew, Shenghan Lin, Bowen Chen et al.
ConnectomeBench: Can LLMs proofread the connectome?
Jeff Brown, Andrew Kirjner, Annika Vivekananthan et al.
Consensus-Robust Transfer Attacks via Parameter and Representation Perturbations
Shixin Li, Zewei Li, Xiaojing Ma et al.
Conservative classifiers do consistently well with improving agents: characterizing statistical and online learning
Dravyansh Sharma, Alec Sun
Consistency Conditions for Differentiable Surrogate Losses
Drona Khurana, Anish Thilagar, Dhamma Kimpara et al.
Consistency of Physics-Informed Neural Networks for Second-Order Elliptic Equations
Yuqian Cheng, Zhuo Chen, Qian Lin
Consistency of the $k_n$-nearest neighbor rule under adaptive sampling
Robi Bhattacharjee, Geelon So, Sanjoy Dasgupta
Consistently Simulating Human Personas with Multi-Turn Reinforcement Learning
Marwa Abdulhai, Ryan Cheng, Donovan Clay et al.
Consistent Paths Lead to Truth: Self-Rewarding Reinforcement Learning for LLM Reasoning
Kongcheng Zhang, QI YAO, Shunyu Liu et al.
Consistent Sampling and Simulation: Molecular Dynamics with Energy-Based Diffusion Models
Michael Plainer, Hao Wu, Leon Klein et al.
Consistent Story Generation: Unlocking the Potential of Zigzag Sampling
Mingxiao Li, Mang Ning, Marie-Francine Moens
Consistent Supervised-Unsupervised Alignment for Generalized Category Discovery
Jizhou Han, Shaokun Wang, Yuhang He et al.
Constant Bit-size Transformers Are Turing Complete
Qian Li, Yuyi Wang
ConStellaration: A dataset of QI-like stellarator plasma boundaries and optimization benchmarks
Santiago Cadena, Andrea Merlo, Emanuel Laude et al.
Constrained Best Arm Identification
Tyron Lardy, Christina Katsimerou, Wouter Koolen
Constrained Diffusers for Safe Planning and Control
Jichen Zhang, Liqun Zhao, Antonis Papachristodoulou et al.
Constrained Discrete Diffusion
Michael Cardei, Jacob K Christopher, Bhavya Kailkhura et al.
Constrained Entropic Unlearning: A Primal-Dual Framework for Large Language Models
Taha Entesari, Arman Hatami, Rinat Khaziev et al.
Constrained Feedback Learning for Non-Stationary Multi-Armed Bandits
Shaoang Li, Jian Li
Constrained Linear Thompson Sampling
Aditya Gangrade, Venkatesh Saligrama
Constrained Optimization From a Control Perspective via Feedback Linearization
Runyu Zhang, Arvind Raghunathan, Jeff Shamma et al.
Constrained Posterior Sampling: Time Series Generation with Hard Constraints
Sai Shankar Narasimhan, Shubhankar Agarwal, Litu Rout et al.
Constrained Sampling for Language Models Should Be Easy: An MCMC Perspective
Emmanuel Anaya Gonzalez, Sairam Vaidya, Kanghee Park et al.