Papers
Practical Sharpness-Aware Minimization Cannot Converge All the Way to Optima
Dongkuk Si, Chulhee Yun
Precision-Recall Divergence Optimization for Generative Modeling with GANs and Normalizing Flows
Alexandre Verine, Benjamin Negrevergne, Muni Sreenivas Pydi et al.
Preconditioning Matters: Fast Global Convergence of Non-convex Matrix Factorization via Scaled Gradient Descent
Xixi Jia, Hailin Wang, Jiangjun Peng et al.
Predicting a Protein's Stability under a Million Mutations
Jeffrey Ouyang-Zhang, Daniel Diaz, Adam Klivans et al.
Predicting Global Label Relationship Matrix for Graph Neural Networks under Heterophily
Langzhang Liang, Xiangjing Hu, Zenglin Xu et al.
Predicting mutational effects on protein-protein binding via a side-chain diffusion probabilistic model
Shiwei Liu, Tian Zhu, Milong Ren et al.
Prediction and Control in Continual Reinforcement Learning
Nishanth Anand, Doina Precup
Predict, Refine, Synthesize: Self-Guiding Diffusion Models for Probabilistic Time Series Forecasting
Marcel Kollovieh, Abdul Fatir Ansari, Michael Bohlke-Schneider et al.
Predict-then-Calibrate: A New Perspective of Robust Contextual LP
Chunlin Sun, Linyu Liu, Xiaocheng Li
PreDiff: Precipitation Nowcasting with Latent Diffusion Models
Zhihan Gao, Xingjian Shi, Boran Han et al.
PRED: Pre-training via Semantic Rendering on LiDAR Point Clouds
Hao Yang, Haiyang Wang, Di Dai et al.
Preference-grounded Token-level Guidance for Language Model Fine-tuning
Shentao Yang, Shujian Zhang, Congying Xia et al.
Prefix-Tree Decoding for Predicting Mass Spectra from Molecules
Samuel Goldman, John Bradshaw, Jiayi Xin et al.
Pre-RMSNorm and Pre-CRMSNorm Transformers: Equivalent and Efficient Pre-LN Transformers
Zixuan Jiang, Jiaqi Gu, Hanqing Zhu et al.
Pre-training Contextualized World Models with In-the-wild Videos for Reinforcement Learning
Jialong Wu, Haoyu Ma, Chaoyi Deng et al.
Pre-Training Protein Encoder via Siamese Sequence-Structure Diffusion Trajectory Prediction
Zuobai Zhang, Minghao Xu, Aurelie C. Lozano et al.
Pretraining task diversity and the emergence of non-Bayesian in-context learning for regression
Allan Raventós, Mansheej Paul, Feng Chen et al.
Primal-Attention: Self-attention through Asymmetric Kernel SVD in Primal Representation
Yingyi Chen, Qinghua Tao, Francesco Tonin et al.
PrimDiffusion: Volumetric Primitives Diffusion for 3D Human Generation
Zhaoxi Chen, Fangzhou Hong, Haiyi Mei et al.
Principle-Driven Self-Alignment of Language Models from Scratch with Minimal Human Supervision
Zhiqing Sun, Yikang Shen, Qinhong Zhou et al.
Principled Weight Initialisation for Input-Convex Neural Networks
Pieter-Jan Hoedt, Günter Klambauer
PriorBand: Practical Hyperparameter Optimization in the Age of Deep Learning
Neeratyoy Mallik, Edward Bergman, Carl Hvarfner et al.
Prioritizing Samples in Reinforcement Learning with Reducible Loss
Shivakanth Sujit, Somjit Nath, Pedro Braga et al.
PRIOR: Personalized Prior for Reactivating the Information Overlooked in Federated Learning.
Mingjia Shi, Yuhao Zhou, Kai Wang et al.