NeurIPS

2021–2025 確定版

著者一覧 · 国際会議 · 大学ランキング

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Machine Learning

2023 · 3,218 papers

このEditionに反映済みのmain full research papersのみ掲載しています。著者リンクは日本の大学への著者別所属根拠がある場合に限ります。

2023 · NeurIPS
Fast Approximation of Similarity Graphs with Kernel Density Estimation
Peter Macgregor, He Sun
Machine Learning
日本大学: 関与なし（対象大学）
2023 · NeurIPS
Fast Asymptotically Optimal Algorithms for Non-Parametric Stochastic Bandits
Dorian Baudry, Fabien Pesquerel, Rémy Degenne, Odalric-Ambrym Maillard
Machine Learning
日本大学: 関与なし（対象大学）
2023 · NeurIPS
Fast Attention Over Long Sequences With Dynamic Sparse Flash Attention
Matteo Pagliardini, Daniele Paliotta, Martin Jaggi, François Fleuret
Machine Learning
日本大学: 関与なし（対象大学）
2023 · NeurIPS
Fast Attention Requires Bounded Entries
Josh Alman, Zhao Song
Machine Learning
日本大学: 関与なし（対象大学）
2023 · NeurIPS
Fast Bellman Updates for Wasserstein Distributionally Robust MDPs
Zhuodong Yu, Ling Dai, Shaohang Xu, Siyang Gao, Chin Pang Ho
Machine Learning
日本大学: 関与なし（対象大学）
2023 · NeurIPS
Fast Conditional Mixing of MCMC Algorithms for Non-log-concave Distributions
Xiang Cheng, Bohan Wang, Jingzhao Zhang, Yusong Zhu
Machine Learning
日本大学: 関与なし（対象大学）
2023 · NeurIPS
Fast Exact Leverage Score Sampling from Khatri-Rao Products with Applications to Tensor Decomposition
Vivek Bharadwaj, Osman Asif Malik, Riley Murray, Laura Grigori, Aydin Buluc, James Demmel
Machine Learning
日本大学: 関与なし（対象大学）
2023 · NeurIPS
Fast Model DeBias with Machine Unlearning
Ruizhe Chen, Jianfei Yang, Huimin Xiong, Jianhong Bai, Tianxiang Hu, Jin Hao, YANG FENG, Joey Tianyi Zhou, Jian Wu, Zuozhu Liu
Machine Learning
日本大学: 関与なし（対象大学）
2023 · NeurIPS
Fast Optimal Locally Private Mean Estimation via Random Projections
Hilal Asi, Vitaly Feldman, Jelani Nelson, Huy Nguyen, Kunal Talwar
Machine Learning
日本大学: 関与なし（対象大学）
2023 · NeurIPS
Fast Optimal Transport through Sliced Generalized Wasserstein Geodesics
Guillaume Mahey, Laetitia Chapel, Gilles Gasso, Clément Bonet, Nicolas Courty
Machine Learning
日本大学: 関与なし（対象大学）
2023 · NeurIPS
Fast Partitioned Learned Bloom Filter
Atsuki Sato, Yusuke Matsui
Machine Learning
日本大学: 東京大学
2023 · NeurIPS
Fast Projected Newton-like Method for Precision Matrix Estimation under Total Positivity
Jian-Feng CAI, José Vinícius de Miranda Cardoso, Daniel Palomar, Jiaxi Ying
Machine Learning
日本大学: 関与なし（対象大学）
2023 · NeurIPS
Fast Rank-1 Lattice Targeted Sampling for Black-box Optimization
Yueming LYU
Machine Learning
日本大学: 関与なし（対象大学）
2023 · NeurIPS
Fast Scalable and Accurate Discovery of DAGs Using the Best Order Score Search and Grow Shrink Trees
Bryan Andrews, Joseph Ramsey, Ruben Sanchez Romero, Jazmin Camchong, Erich Kummerfeld
Machine Learning
日本大学: 関与なし（対象大学）
2023 · NeurIPS
Fast Trainable Projection for Robust Fine-tuning
Junjiao Tian, Yen-Cheng Liu, James S Smith, Zsolt Kira
Machine Learning
日本大学: 関与なし（対象大学）
2023 · NeurIPS
Fast and Regret Optimal Best Arm Identification: Fundamental Limits and Low-Complexity Algorithms
Qining Zhang, Lei Ying
Machine Learning
日本大学: 関与なし（対象大学）
2023 · NeurIPS
Fast and Simple Spectral Clustering in Theory and Practice
Peter Macgregor
Machine Learning
日本大学: 関与なし（対象大学）
2023 · NeurIPS
Faster Differentially Private Convex Optimization via Second-Order Methods
Arun Ganesh, Mahdi Haghifam, Thomas Steinke, Abhradeep Guha Thakurta
Machine Learning
日本大学: 関与なし（対象大学）
2023 · NeurIPS
Faster Discrete Convex Function Minimization with Predictions: The M-Convex Case
Taihei Oki, Shinsaku Sakaue
Machine Learning
日本大学: 東京大学
2023 · NeurIPS
Faster Margin Maximization Rates for Generic Optimization Methods
Guanghui Wang, Zihao Hu, Vidya Muthukumar, Jacob D. Abernethy
Machine Learning
日本大学: 関与なし（対象大学）
2023 · NeurIPS
Faster Query Times for Fully Dynamic $k$-Center Clustering with Outliers
Leyla Biabani, Annika Hennes, Morteza Monemizadeh, Melanie Schmidt
Machine Learning
日本大学: 関与なし（対象大学）
2023 · NeurIPS
Faster Relative Entropy Coding with Greedy Rejection Coding
Gergely Flamich, Stratis Markou, José Miguel Hernández-Lobato
Machine Learning
日本大学: 関与なし（対象大学）
2023 · NeurIPS
Faster approximate subgraph counts with privacy
Dung Nguyen, Mahantesh Halappanavar, Venkatesh Srinivasan, Anil Vullikanti
Machine Learning
日本大学: 関与なし（対象大学）
2023 · NeurIPS
FeCAM: Exploiting the Heterogeneity of Class Distributions in Exemplar-Free Continual Learning
Dipam Goswami, Yuyang Liu, Bartłomiej Twardowski, Joost van de Weijer
Machine Learning
日本大学: 関与なし（対象大学）
2023 · NeurIPS
Feature Adaptation for Sparse Linear Regression
Jonathan Kelner, Frederic Koehler, Raghu Meka, Dhruv Rohatgi
Machine Learning
日本大学: 関与なし（対象大学）
2023 · NeurIPS
Feature Dropout: Revisiting the Role of Augmentations in Contrastive Learning
Alex Tamkin, Margalit Glasgow, Xiluo He, Noah Goodman
Machine Learning
日本大学: 関与なし（対象大学）
2023 · NeurIPS
Feature Learning for Interpretable, Performant Decision Trees
Jack Good, Torin Kovach, Kyle Miller, Artur Dubrawski
Machine Learning
日本大学: 関与なし（対象大学）
2023 · NeurIPS
Feature Likelihood Divergence: Evaluating the Generalization of Generative Models Using Samples
Marco Jiralerspong, Joey Bose, Ian Gemp, Chongli Qin, Yoram Bachrach, Gauthier Gidel
Machine Learning
日本大学: 関与なし（対象大学）
2023 · NeurIPS
Feature Selection in the Contrastive Analysis Setting
Ethan Weinberger, Ian Covert, Su-In Lee
Machine Learning
日本大学: 関与なし（対象大学）
2023 · NeurIPS
Feature learning via mean-field Langevin dynamics: classifying sparse parities and beyond
Taiji Suzuki, Denny Wu, Kazusato Oko, Atsushi Nitanda
Machine Learning
日本大学: 東京大学
2023 · NeurIPS
Feature-Learning Networks Are Consistent Across Widths At Realistic Scales
Nikhil Vyas, Alexander Atanasov, Blake Bordelon, Depen Morwani, Sabarish Sainathan, Cengiz Pehlevan
Machine Learning
日本大学: 関与なし（対象大学）
2023 · NeurIPS
Fed-CO$_{2}$: Cooperation of Online and Offline Models for Severe Data Heterogeneity in Federated Learning
Zhongyi Cai, Ye Shi, Wei Huang, Jingya Wang
Machine Learning
日本大学: 関与なし（対象大学）
2023 · NeurIPS
Fed-FA: Theoretically Modeling Client Data Divergence for Federated Language Backdoor Defense
Zhiyuan Zhang, Deli Chen, Hao Zhou, Fandong Meng, Jie Zhou, Xu Sun
Machine Learning
日本大学: 関与なし（対象大学）
2023 · NeurIPS
Fed-GraB: Federated Long-tailed Learning with Self-Adjusting Gradient Balancer
Zikai Xiao, Zihan Chen, Songshang Liu, Hualiang Wang, YANG FENG, Jin Hao, Joey Tianyi Zhou, Jian Wu, Howard Hua Yang, Zuozhu Liu
Machine Learning
日本大学: 関与なし（対象大学）
2023 · NeurIPS
FedFed: Feature Distillation against Data Heterogeneity in Federated Learning
Zhiqin Yang, Yonggang Zhang, Yu Zheng, Xinmei Tian, Hao Peng, Tongliang Liu, Bo Han
Machine Learning
日本大学: 関与なし（対象大学）
2023 · NeurIPS
FedGCN: Convergence-Communication Tradeoffs in Federated Training of Graph Convolutional Networks
Yuhang Yao, Weizhao Jin, Srivatsan Ravi, Carlee Joe-Wong
Machine Learning
日本大学: 関与なし（対象大学）
2023 · NeurIPS
FedGame: A Game-Theoretic Defense against Backdoor Attacks in Federated Learning
Jinyuan Jia, Zhuowen Yuan, Dinuka Sahabandu, Luyao Niu, Arezoo Rajabi, Bhaskar Ramasubramanian, Bo Li, Radha Poovendran
Machine Learning
日本大学: 関与なし（対象大学）
2023 · NeurIPS
FedL2P: Federated Learning to Personalize
Royson Lee, Minyoung Kim, Da Li, Xinchi Qiu, Timothy Hospedales, Ferenc Huszar, Nicholas Lane
Machine Learning
日本大学: 関与なし（対象大学）
2023 · NeurIPS
FedNAR: Federated Optimization with Normalized Annealing Regularization
Junbo Li, Ang Li, Chong Tian, Qirong Ho, Eric P. Xing, Hongyi Wang
Machine Learning
日本大学: 関与なし（対象大学）
2023 · NeurIPS
Federated Compositional Deep AUC Maximization
Xinwen Zhang, Yihan Zhang, Tianbao Yang, Richard Souvenir, Hongchang Gao
Machine Learning
日本大学: 関与なし（対象大学）
2023 · NeurIPS
Federated Conditional Stochastic Optimization
Xidong Wu, Jianhui Sun, Zhengmian Hu, Junyi Li, Aidong Zhang, Heng Huang
Machine Learning
日本大学: 関与なし（対象大学）
2023 · NeurIPS
Federated Learning via Meta-Variational Dropout
Insu Jeon, Minui Hong, Junhyeog Yun, Gunhee Kim
Machine Learning
日本大学: 関与なし（対象大学）
2023 · NeurIPS
Federated Learning with Bilateral Curation for Partially Class-Disjoint Data
Ziqing Fan, ruipeng zhang, Jiangchao Yao, Bo Han, Ya Zhang, Yanfeng Wang
Machine Learning
日本大学: 関与なし（対象大学）
2023 · NeurIPS
Federated Learning with Client Subsampling, Data Heterogeneity, and Unbounded Smoothness: A New Algorithm and Lower Bounds
Michael Crawshaw, Yajie Bao, Mingrui Liu
Machine Learning
日本大学: 関与なし（対象大学）
2023 · NeurIPS
Federated Learning with Manifold Regularization and Normalized Update Reaggregation
Xuming An, Li Shen, Han Hu, Yong Luo
Machine Learning
日本大学: 関与なし（対象大学）
2023 · NeurIPS
Federated Linear Bandits with Finite Adversarial Actions
Li Fan, Ruida Zhou, Chao Tian, Cong Shen
Machine Learning
日本大学: 関与なし（対象大学）
2023 · NeurIPS
Federated Multi-Objective Learning
Haibo Yang, Zhuqing Liu, Jia Liu, Chaosheng Dong, Michinari Momma
Machine Learning
日本大学: 関与なし（対象大学）
2023 · NeurIPS
Federated Spectral Clustering via Secure Similarity Reconstruction
Dong Qiao, Chris Ding, Jicong Fan
Machine Learning
日本大学: 関与なし（対象大学）
2023 · NeurIPS
Few-Shot Class-Incremental Learning via Training-Free Prototype Calibration
Qi-Wei Wang, Da-Wei Zhou, Yi-Kai Zhang, De-Chuan Zhan, Han-Jia Ye
Machine Learning
日本大学: 関与なし（対象大学）
2023 · NeurIPS
Few-shot Generation via Recalling Brain-Inspired Episodic-Semantic Memory
Zhibin Duan, Zhiyi Lv, Chaojie Wang, Bo Chen, Bo An, Mingyuan Zhou
Machine Learning
日本大学: 関与なし（対象大学）
2023 · NeurIPS
FiGURe: Simple and Efficient Unsupervised Node Representations with Filter Augmentations
Chanakya Ekbote, Ajinkya Deshpande, Arun Iyer, SUNDARARAJAN SELLAMANICKAM, Ramakrishna Bairi
Machine Learning
日本大学: 関与なし（対象大学）
2023 · NeurIPS
Find What You Want: Learning Demand-conditioned Object Attribute Space for Demand-driven Navigation
Hongcheng Wang, Andy Guan Hong Chen, Xiaoqi Li, Mingdong Wu, Hao Dong
Machine Learning
日本大学: 関与なし（対象大学）
2023 · NeurIPS
Finding Counterfactually Optimal Action Sequences in Continuous State Spaces
Stratis Tsirtsis, Manuel Rodriguez
Machine Learning
日本大学: 関与なし（対象大学）
2023 · NeurIPS
Finding Local Minima Efficiently in Decentralized Optimization
Wenhan Xian, Heng Huang
Machine Learning
日本大学: 関与なし（対象大学）
2023 · NeurIPS
Finding Order in Chaos: A Novel Data Augmentation Method for Time Series in Contrastive Learning
Berken Utku Demirel, Christian Holz
Machine Learning
日本大学: 関与なし（対象大学）
2023 · NeurIPS
Finding Safe Zones of Markov Decision Processes Policies
Lee Cohen, Yishay Mansour, Michal Moshkovitz
Machine Learning
日本大学: 関与なし（対象大学）
2023 · NeurIPS
Fine-Grained Cross-View Geo-Localization Using a Correlation-Aware Homography Estimator
Xiaolong Wang, Runsen Xu, Zhuofan Cui, Zeyu Wan, Yu Zhang
Machine Learning
日本大学: 関与なし（対象大学）
2023 · NeurIPS
Fine-Grained Human Feedback Gives Better Rewards for Language Model Training
Zeqiu Wu, Yushi Hu, Weijia Shi, Nouha Dziri, Alane Suhr, Prithviraj Ammanabrolu, Noah A. Smith, Mari Ostendorf, Hannaneh Hajishirzi
Machine Learning
日本大学: 関与なし（対象大学）
2023 · NeurIPS
Fine-Grained Theoretical Analysis of Federated Zeroth-Order Optimization
Jun Chen, Hong Chen, Bin Gu, Hao Deng
Machine Learning
日本大学: 関与なし（対象大学）
2023 · NeurIPS
Fine-Grained Visual Prompting
Lingfeng Yang, Yueze Wang, Xiang Li, Xinlong Wang, Jian Yang
Machine Learning
日本大学: 関与なし（対象大学）
2023 · NeurIPS
Fine-Tuning Language Models with Just Forward Passes
Sadhika Malladi, Tianyu Gao, Eshaan Nichani, Alex Damian, Jason Lee, Danqi Chen, Sanjeev Arora
Machine Learning
日本大学: 関与なし（対象大学）
2023 · NeurIPS
Fine-grained Expressivity of Graph Neural Networks
Jan Böker, Ron Levie, Ningyuan Huang, Soledad Villar, Christopher Morris
Machine Learning
日本大学: 関与なし（対象大学）
2023 · NeurIPS
Fine-grained Late-interaction Multi-modal Retrieval for Retrieval Augmented Visual Question Answering
Weizhe Lin, Jinghong Chen, Jingbiao Mei, Alexandru Coca, Bill Byrne
Machine Learning
日本大学: 関与なし（対象大学）
2023 · NeurIPS
FineMoGen: Fine-Grained Spatio-Temporal Motion Generation and Editing
Mingyuan Zhang, Huirong Li, Zhongang Cai, Jiawei Ren, Lei Yang, Ziwei Liu
Machine Learning
日本大学: 関与なし（対象大学）
2023 · NeurIPS
Finite Population Regression Adjustment and Non-asymptotic Guarantees for Treatment Effect Estimation
Mehrdad Ghadiri, David Arbour, Tung Mai, Cameron Musco, Anup B. Rao
Machine Learning
日本大学: 関与なし（対象大学）
2023 · NeurIPS
Finite-Time Analysis of Single-Timescale Actor-Critic
Xuyang Chen, Lin Zhao
Machine Learning
日本大学: 関与なし（対象大学）
2023 · NeurIPS
Finite-Time Analysis of Whittle Index based Q-Learning for Restless Multi-Armed Bandits with Neural Network Function Approximation
GUOJUN XIONG, Jian Li
Machine Learning
日本大学: 関与なし（対象大学）
2023 · NeurIPS
Finite-Time Logarithmic Bayes Regret Upper Bounds
Alexia Atsidakou, Branislav Kveton, Sumeet Katariya, Constantine Caramanis, Sujay Sanghavi
Machine Learning
日本大学: 関与なし（対象大学）
2023 · NeurIPS
First Order Methods with Markovian Noise: from Acceleration to Variational Inequalities
Aleksandr Beznosikov, Sergey Samsonov, Marina Sheshukova, Alexander Gasnikov, Alexey Naumov, Eric Moulines
Machine Learning
日本大学: 関与なし（対象大学）
2023 · NeurIPS
First Order Stochastic Optimization with Oblivious Noise
Ilias Diakonikolas, Sushrut Karmalkar, Jong Ho Park, Christos Tzamos
Machine Learning
日本大学: 関与なし（対象大学）
2023 · NeurIPS
First- and Second-Order Bounds for Adversarial Linear Contextual Bandits
Julia Olkhovskaya, Jack Mayo, Tim van Erven, Gergely Neu, Chen-Yu Wei
Machine Learning
日本大学: 関与なし（対象大学）
2023 · NeurIPS
Fitting trees to $\ell_1$-hyperbolic distances
Joon-Hyeok Yim, Anna Gilbert
Machine Learning
日本大学: 関与なし（対象大学）
2023 · NeurIPS
Fixing the NTK: From Neural Network Linearizations to Exact Convex Programs
Rajat Vadiraj Dwaraknath, Tolga Ergen, Mert Pilanci
Machine Learning
日本大学: 関与なし（対象大学）
2023 · NeurIPS
Flat Seeking Bayesian Neural Networks
Van-Anh Nguyen, Tung-Long Vuong, Hoang Phan, Thanh-Toan Do, Dinh Phung, Trung Le
Machine Learning
日本大学: 関与なし（対象大学）
2023 · NeurIPS
FlatMatch: Bridging Labeled Data and Unlabeled Data with Cross-Sharpness for Semi-Supervised Learning
Zhuo Huang, Li Shen, Jun Yu, Bo Han, Tongliang Liu
Machine Learning
日本大学: 関与なし（対象大学）
2023 · NeurIPS
Flexible Attention-Based Multi-Policy Fusion for Efficient Deep Reinforcement Learning
Zih-Yun Chiu, Yi-Lin Tuan, William Yang Wang, Michael Yip
Machine Learning
日本大学: 関与なし（対象大学）
2023 · NeurIPS
Flocks of Stochastic Parrots: Differentially Private Prompt Learning for Large Language Models
Haonan Duan, Adam Dziedzic, Nicolas Papernot, Franziska Boenisch
Machine Learning
日本大学: 関与なし（対象大学）
2023 · NeurIPS
Flow Factorized Representation Learning
Yue Song, Andy Keller, Nicu Sebe, Max Welling
Machine Learning
日本大学: 関与なし（対象大学）
2023 · NeurIPS
Flow Matching for Scalable Simulation-Based Inference
Jonas Wildberger, Maximilian Dax, Simon Buchholz, Stephen Green, Jakob H Macke, Bernhard Schölkopf
Machine Learning
日本大学: 関与なし（対象大学）
2023 · NeurIPS
Flow-Attention-based Spatio-Temporal Aggregation Network for 3D Mask Detection
Yuxin Cao, Yian Li, Yumeng Zhu, Derui Wang, Minhui Xue
Machine Learning
日本大学: 関与なし（対象大学）
2023 · NeurIPS
Flow-Based Feature Fusion for Vehicle-Infrastructure Cooperative 3D Object Detection
Haibao Yu, Yingjuan Tang, Enze Xie, Jilei Mao, Ping Luo, Zaiqing Nie
Machine Learning
日本大学: 関与なし（対象大学）
2023 · NeurIPS
Flow: Per-instance Personalized Federated Learning
Kunjal Panchal, Sunav Choudhary, Nisarg Parikh, Lijun Zhang, Hui Guan
Machine Learning
日本大学: 関与なし（対象大学）
2023 · NeurIPS
FlowCam: Training Generalizable 3D Radiance Fields without Camera Poses via Pixel-Aligned Scene Flow
Cameron Smith, Yilun Du, Ayush Tewari, Vincent Sitzmann
Machine Learning
日本大学: 関与なし（対象大学）
2023 · NeurIPS
FlowPG: Action-constrained Policy Gradient with Normalizing Flows
Janaka Brahmanage, Jiajing LING, Akshat Kumar
Machine Learning
日本大学: 関与なし（対象大学）
2023 · NeurIPS
Focus Your Attention when Few-Shot Classification
Haoqing Wang, Shibo Jie, Zhihong Deng
Machine Learning
日本大学: 関与なし（対象大学）
2023 · NeurIPS
Focus on Query: Adversarial Mining Transformer for Few-Shot Segmentation
Yuan Wang, Naisong Luo, Tianzhu Zhang
Machine Learning
日本大学: 関与なし（対象大学）
2023 · NeurIPS
Focused Transformer: Contrastive Training for Context Scaling
Szymon Tworkowski, Konrad Staniszewski, Mikołaj Pacek, Yuhuai Wu, Henryk Michalewski, Piotr Miłoś
Machine Learning
日本大学: 関与なし（対象大学）
2023 · NeurIPS
Follow-ups Also Matter: Improving Contextual Bandits via Post-serving Contexts
Chaoqi Wang, Ziyu Ye, Zhe Feng, Ashwinkumar Badanidiyuru Varadaraja, Haifeng Xu
Machine Learning
日本大学: 関与なし（対象大学）
2023 · NeurIPS
For SALE: State-Action Representation Learning for Deep Reinforcement Learning
Scott Fujimoto, Wei-Di Chang, Edward Smith, Shixiang (Shane) Gu, Doina Precup, David Meger
Machine Learning
日本大学: 関与なし（対象大学）
2023 · NeurIPS
ForecastPFN: Synthetically-Trained Zero-Shot Forecasting
Samuel Dooley, Gurnoor Singh Khurana, Chirag Mohapatra, Siddartha V Naidu, Colin White
Machine Learning
日本大学: 関与なし（対象大学）
2023 · NeurIPS
ForkMerge: Mitigating Negative Transfer in Auxiliary-Task Learning
Junguang Jiang, Baixu Chen, Junwei Pan, Ximei Wang, Dapeng Liu, Jie Jiang, Mingsheng Long
Machine Learning
日本大学: 関与なし（対象大学）
2023 · NeurIPS
Formalizing locality for normative synaptic plasticity models
Colin Bredenberg, Ezekiel Williams, Cristina Savin, Blake Richards, Guillaume Lajoie
Machine Learning
日本大学: 関与なし（対象大学）
2023 · NeurIPS
Formulating Discrete Probability Flow Through Optimal Transport
Pengze Zhang, Hubery Yin, Chen Li, Xiaohua Xie
Machine Learning
日本大学: 関与なし（対象大学）
2023 · NeurIPS
Foundation Model is Efficient Multimodal Multitask Model Selector
Fanqing Meng, Wenqi Shao, zhanglin peng, Chonghe Jiang, Kaipeng Zhang, Yu Qiao, Ping Luo
Machine Learning
日本大学: 東京大学
2023 · NeurIPS
FouriDown: Factoring Down-Sampling into Shuffling and Superposing
Qi Zhu, man zhou, Jie Huang, Naishan Zheng, Hongzhi Gao, Chongyi Li, Yuan Xu, Feng Zhao
Machine Learning
日本大学: 関与なし（対象大学）
2023 · NeurIPS
FourierGNN: Rethinking Multivariate Time Series Forecasting from a Pure Graph Perspective
Kun Yi, Qi Zhang, Wei Fan, Hui He, Liang Hu, Pengyang Wang, Ning An, Longbing Cao, Zhendong Niu
Machine Learning
日本大学: 関与なし（対象大学）
2023 · NeurIPS
FourierHandFlow: Neural 4D Hand Representation Using Fourier Query Flow
Jihyun Lee, Junbong Jang, Donghwan Kim, Minhyuk Sung, Tae-Kyun Kim
Machine Learning
日本大学: 関与なし（対象大学）
2023 · NeurIPS
Fractal Landscapes in Policy Optimization
Tao Wang, Sylvia Herbert, Sicun Gao
Machine Learning
日本大学: 関与なし（対象大学）
2023 · NeurIPS
Fragment-based Pretraining and Finetuning on Molecular Graphs
Kha-Dinh Luong, Ambuj K Singh
Machine Learning
日本大学: 関与なし（対象大学）
2023 · NeurIPS
Free-Bloom: Zero-Shot Text-to-Video Generator with LLM Director and LDM Animator
Hanzhuo Huang, Yufan Feng, Cheng Shi, Lan Xu, Jingyi Yu, Sibei Yang
Machine Learning
日本大学: 関与なし（対象大学）