Neural Information Processing Systems Foundation, Inc. (NeurIPS)

Neural Information Processing Systems Foundation, Inc. (NeurIPS)

Physics-Informed Bayesian Optimization of Variational Quantum Circuits

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

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Physics-Informed Implicit Representations of Equilibrium Network Flows

Kevin D. Smith, Francesco Seccamonte, Ananthram Swami, Francesco Bullo 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

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

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Physics-Informed Variational State-Space Gaussian Processes

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

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

Michal Balcerak, Tamaz Amiranashvili, Andreas Wagner, Jonas Weidner, Petr Karnakov, Johannes Paetzold, Ivan Ezhov, Petros Koumoutsakos, Benedikt Wiestler, Bjoern Menze 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

Hsiao-Yu Tung, Mingyu Ding, Zhenfang Chen, Daniel Bear, Chuang Gan, Josh Tenenbaum, Dan Yamins, Judith Fan, Kevin Smith 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, Adam Polyak, Uriel Singer, Shahbuland Matiana, Joe Penna, Omer Levy 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, Ananya Kumar, Dan Jurafsky, Percy Liang p3663-3678 from Advances in Neural Information Processing Systems 35

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PICProp: Physics-Informed Confidence Propagation for Uncertainty Quantification

Qianli Shen, Wai Hoh Tang, Zhun Deng, Apostolos Psaros, Kenji Kawaguchi 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, Dario Shariatian, Umut Simsekli, Eric Moulines, Alain Durmus p93336-93373 from Advances in Neural Information Processing Systems 37

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Piecewise-Stationary Bandits with Knapsacks

Xilin Zhang, Cheung Wang 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

Peter Henderson, Mark Krass, Lucia Zheng, Neel Guha, Christopher D Manning, Dan Jurafsky, Daniel Ho 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

Liang Wang, Qiang Liu, Shaozhen Liu, Xin Sun, Shu Wu, Liang Wang 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, Jiachen Yao, Chang Su, Hang Su, Ziao Wang, Fanzhi Lu, Zeyu Xia, Yichi Zhang, Songming Liu, Lu Lu, Jun Zhu p76721-76774 from Advances in Neural Information Processing Systems 37

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Pipeline Parallelism with Controllable Memory

Penghui Qi, Xinyi Wan, Nyamdavaa Amar, Min Lin 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, Kyungjae Lee, Jungwoo 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

Kaidong Zhang, Pengzhen Ren, Bingqian Lin, Junfan Lin, Shikui Ma, Hang Xu, Xiaodan Liang 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

Qianqian Xie, Weiguang Han, Xiao Zhang, Yanzhao Lai, Min Peng, Alejandro Lopez-Lira, Jimin Huang 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, Yifan Zhang, Jianfei Gao, Anda Cheng, Ke Cheng, Jian Cheng 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

Zifan Wu, Chao Yu, Chen Chen, Jianye Hao, 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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