Neural Information Processing Systems Foundation, Inc. (NeurIPS)

Neural Information Processing Systems Foundation, Inc. (NeurIPS)

Physics-Informed Bayesian Optimization of Variational Quantum Circuits

Christopher J. Anders, Lena Funcke, Tobias Hartung, Karl Jansen, Pan Kessel, Stefan Kühn, Klaus-Robert Müller, Shinichi Nakajima, Kim Nicoli, Paolo Stornati p18341-18376 from Advances in Neural Information Processing Systems 36

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Physics-Informed Implicit Representations of Equilibrium Network Flows

Francesco Bullo, Francesco Seccamonte, Kevin D. Smith, Ananthram Swami p7211-7221 from Advances in Neural Information Processing Systems 35

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Physics-informed Neural Networks for Functional Differential Equations: Cylindrical Approximation and Its Convergence Guarantees

Taiki Miyagawa, Takeru Yokota p72274-72409 from Advances in Neural Information Processing Systems 37

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Physics-Informed Regularization for Domain-Agnostic Dynamical System Modeling

Yadi Cao, Yuanzhou Chen, Jingdong Gao, Ziniu Hu, Zijie Huang, Xiao Luo, Yizhou Sun, Wei Wang, Wanjia Zhao p739-774 from Advances in Neural Information Processing Systems 37

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Physics-Informed Variational State-Space Gaussian Processes

Theodoros Damoulas, Oliver Hamelijnck, Arno Solin p98505-98536 from Advances in Neural Information Processing Systems 37

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Physics-Regularized Multi-Modal Image Assimilation for Brain Tumor Localization

Tamaz Amiranashvili, Michal Balcerak, Ivan Ezhov, Petr Karnakov, Petros Koumoutsakos, Bjoern Menze, Johannes Paetzold, Andreas Wagner, Jonas Weidner, Benedikt Wiestler p41909-41933 from Advances in Neural Information Processing Systems 37

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Physion++: Evaluating Physical Scene Understanding that Requires Online Inference of Different Physical Properties

Daniel Bear, Zhenfang Chen, Mingyu Ding, Judith Fan, Chuang Gan, Kevin Smith, Josh Tenenbaum, Hsiao-Yu Tung, Dan Yamins p67048-67068 from Advances in Neural Information Processing Systems 36

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Pick-a-Pic: An Open Dataset of User Preferences for Text-to-Image Generation

Yuval Kirstain, Omer Levy, Shahbuland Matiana, Joe Penna, Adam Polyak, Uriel Singer p36652-36663 from Advances in Neural Information Processing Systems 36

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Picking on the Same Person: Does Algorithmic Monoculture Lead to Outcome Homogenization?

Rishi Bommasani, Kathleen A. Creel, Dan Jurafsky, Ananya Kumar, Percy Liang p3663-3678 from Advances in Neural Information Processing Systems 35

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PICProp: Physics-Informed Confidence Propagation for Uncertainty Quantification

Zhun Deng, Kenji Kawaguchi, Apostolos Psaros, Qianli Shen, Wai Hoh Tang p33041-33064 from Advances in Neural Information Processing Systems 36

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PID-Inspired Inductive Biases for Deep Reinforcement Learning in Partially Observable Control Tasks

Ian Char, Jeff Schneider p59425-59463 from Advances in Neural Information Processing Systems 36

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Piecewise deterministic generative models

Andrea Bertazzi, Alain Durmus, Eric Moulines, Dario Shariatian, Umut Simsekli p93336-93373 from Advances in Neural Information Processing Systems 37

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Piecewise-Stationary Bandits with Knapsacks

Cheung Wang, Xilin Zhang p56001-56040 from Advances in Neural Information Processing Systems 37

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Pile of Law: Learning Responsible Data Filtering from the Law and a 256GB Open-Source Legal Dataset

Neel Guha, Peter Henderson, Daniel Ho, Dan Jurafsky, Mark Krass, Christopher D Manning, Lucia Zheng p29217-29234 from Advances in Neural Information Processing Systems 35

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Pin-Tuning: Parameter-Efficient In-Context Tuning for Few-Shot Molecular Property Prediction

Qiang Liu, Shaozhen Liu, Xin Sun, Liang Wang, Liang Wang, Shu Wu p70765-70792 from Advances in Neural Information Processing Systems 37

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PINNacle: A Comprehensive Benchmark of Physics-Informed Neural Networks for Solving PDEs

Zhongkai Hao, Songming Liu, Fanzhi Lu, Lu Lu, Chang Su, Hang Su, Ziao Wang, Zeyu Xia, Jiachen Yao, Yichi Zhang, Jun Zhu p76721-76774 from Advances in Neural Information Processing Systems 37

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Pipeline Parallelism with Controllable Memory

Nyamdavaa Amar, Min Lin, Penghui Qi, Xinyi Wan p46539-46566 from Advances in Neural Information Processing Systems 37

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PiSSA: Principal Singular Values and Singular Vectors Adaptation of Large Language Models

Fanxu Meng, Zhaohui Wang, Muhan Zhang p121038-121072 from Advances in Neural Information Processing Systems 37

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Pitfall of Optimism: Distributional Reinforcement Learning by Randomizing Risk Criterion

Taehyun Cho, Seungyub Han, Heesoo Lee, Jungwoo Lee, Kyungjae Lee p56802-56824 from Advances in Neural Information Processing Systems 36

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Pitfalls of Epistemic Uncertainty Quantification Through Loss Minimisation

Viktor Bengs, Eyke Hüllermeier, Willem Waegeman p29205-29216 from Advances in Neural Information Processing Systems 35

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Neural Information Processing Systems Foundation, Inc. (NeurIPS)

PIVOT-R: Primitive-Driven Waypoint-Aware World Model for Robotic Manipulation

Xiaodan Liang, Bingqian Lin, Junfan Lin, Shikui Ma, Pengzhen Ren, Hang Xu, Kaidong Zhang p54105-54136 from Advances in Neural Information Processing Systems 37

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PIXIU: A Comprehensive Benchmark, Instruction Dataset and Large Language Model for Finance

Weiguang Han, Jimin Huang, Yanzhao Lai, Alejandro Lopez-Lira, Min Peng, Qianqian Xie, Xiao Zhang p33469-33484 from Advances in Neural Information Processing Systems 36

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PKD: General Distillation Framework for Object Detectors Via Pearson Correlation Coefficient

Weihan Cao, Anda Cheng, Jian Cheng, Ke Cheng, Jianfei Gao, Yifan Zhang p15394-15406 from Advances in Neural Information Processing Systems 35

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Plan to Predict: Learning an Uncertainty-Foreseeing Model for Model-Based Reinforcement Learning

Chen Chen, Jianye Hao, Zifan Wu, Chao Yu, Hankz Hankui Zhuo p15849-15861 from Advances in Neural Information Processing Systems 35

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Neural Information Processing Systems Foundation, Inc. (NeurIPS)

Physics-Informed Bayesian Optimization of Variational Quantum Circuits

Physics-Informed Implicit Representations of Equilibrium Network Flows

Physics-informed Neural Networks for Functional Differential Equations: Cylindrical Approximation and Its Convergence Guarantees

Physics-Informed Regularization for Domain-Agnostic Dynamical System Modeling

Physics-Informed Variational State-Space Gaussian Processes

Physics-Regularized Multi-Modal Image Assimilation for Brain Tumor Localization

Physion++: Evaluating Physical Scene Understanding that Requires Online Inference of Different Physical Properties

Pick-a-Pic: An Open Dataset of User Preferences for Text-to-Image Generation

Picking on the Same Person: Does Algorithmic Monoculture Lead to Outcome Homogenization?

PICProp: Physics-Informed Confidence Propagation for Uncertainty Quantification

PID-Inspired Inductive Biases for Deep Reinforcement Learning in Partially Observable Control Tasks

Piecewise deterministic generative models

Piecewise-Stationary Bandits with Knapsacks

Pile of Law: Learning Responsible Data Filtering from the Law and a 256GB Open-Source Legal Dataset

Pin-Tuning: Parameter-Efficient In-Context Tuning for Few-Shot Molecular Property Prediction

PINNacle: A Comprehensive Benchmark of Physics-Informed Neural Networks for Solving PDEs

Pipeline Parallelism with Controllable Memory

PiSSA: Principal Singular Values and Singular Vectors Adaptation of Large Language Models

Pitfall of Optimism: Distributional Reinforcement Learning by Randomizing Risk Criterion

Pitfalls of Epistemic Uncertainty Quantification Through Loss Minimisation

PIVOT-R: Primitive-Driven Waypoint-Aware World Model for Robotic Manipulation

PIXIU: A Comprehensive Benchmark, Instruction Dataset and Large Language Model for Finance

PKD: General Distillation Framework for Object Detectors Via Pearson Correlation Coefficient

Plan to Predict: Learning an Uncertainty-Foreseeing Model for Model-Based Reinforcement Learning

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