NeurIPS

Unifying Interpretability and Explainability for Alzheimer's Disease Progression Prediction

Raja Farrukh Ali, Stephanie Milani, John Woods, Emmanuel Adenij, Ayesha Farooq, Clayton Mansel, Jeffrey Burns, William Hsu

Comments Previous versions accepted to NeurIPS 2023's XAIA and AAAI 2024's XAI4DRL workshops

Multi-Constitutive Neural Network for Large Deformation Poromechanics Problem

Qi Zhang, Yilin Chen, Ziyi Yang, Eric Darve

Comments Camera-ready (final) paper of the Third Workshop on Machine Learning and the Physical Sciences (NeurIPS 2020), Vancouver. Add more figures despite the workshop is closed

Journal ref Machine Learning and the Physical Sciences workshop, NeurIPS (2020) 96

Physics-Informed Bayesian Optimization of Variational Quantum Circuits

Kim A. Nicoli, Christopher J. Anders, Lena Funcke, Tobias Hartung, Karl Jansen, Stefan Kühn, Klaus-Robert Müller, Paolo Stornati, Pan Kessel, Shinichi Nakajima

Comments 36 pages, 17 figures, 37th Conference on Neural Information Processing Systems (NeurIPS 2023)

Perturbation Towards Easy Samples Improves Targeted Adversarial Transferability

Junqi Gao, Biqing Qi, Yao Li, Zhichang Guo, Dong Li, Yuming Xing, Dazhi Zhang

Journal ref Advances in Neural Information Processing Systems 36, 2023

Equivariant Spatio-Temporal Attentive Graph Networks to Simulate Physical Dynamics

Liming Wu, Zhichao Hou, Jirui Yuan, Yu Rong, Wenbing Huang

Comments The paper has been published to the conference of NeurIPS 2023

Breeding Programs Optimization with Reinforcement Learning

Omar G. Younis, Luca Corinzia, Ioannis N. Athanasiadis, Andreas Krause, Joachim M. Buhmann, Matteo Turchetta

Comments NeurIPS 2023 Workshop on Tackling Climate Change with Machine Learning

Structured Voronoi Sampling

Afra Amini, Li Du, Ryan Cotterell

Comments Accepted at NeurIPS 2023

Challenging the Validity of Personality Tests for Large Language Models

Tom Sühr, Florian E. Dorner, Samira Samadi, Augustin Kelava

Comments A less extensive and shorter version of this work has been accepted at Socially Responsible Language Modelling Research (SoLaR) 2023 Workshop at NeurIPS 2023

GenS: Generalizable Neural Surface Reconstruction from Multi-View Images

Rui Peng, Xiaodong Gu, Luyang Tang, Shihe Shen, Fanqi Yu, Ronggang Wang

Comments NeurIPS 2023 Accepted

Improving Diffusion-Based Image Synthesis with Context Prediction

Ling Yang, Jingwei Liu, Shenda Hong, Zhilong Zhang, Zhilin Huang, Zheming Cai, Wentao Zhang, Bin Cui

Comments Accepted by NeurIPS 2023

Text Promptable Surgical Instrument Segmentation with Vision-Language Models

Zijian Zhou, Oluwatosin Alabi, Meng Wei, Tom Vercauteren, Miaojing Shi

Comments NeurIPS 2023

Journal ref https://proceedings.neurips.cc/paper_files/paper/2023/hash/5af741d487c5f0b08bfe56e11d1883e4-Abstract-Conference.html

Demystifying Oversmoothing in Attention-Based Graph Neural Networks

Xinyi Wu, Amir Ajorlou, Zihui Wu, Ali Jadbabaie

Comments NeurIPS 2023 spotlight. Fixed an error in the previous version; new results and remarks added

A Monte Carlo Language Model Pipeline for Zero-Shot Sociopolitical Event Extraction

Erica Cai, Brendan O'Connor

Comments Accepted at NeurIPS 2023 Workshop on Instruction Tuning and Instruction Following; oral presentation at New England Natural Language Processing, 2023; 17 pages of text including references and appendix

Weak Augmentation Guided Relational Self-Supervised Learning

Mingkai Zheng, Shan You, Fei Wang, Chen Qian, Changshui Zhang, Xiaogang Wang, Chang Xu

Comments Extended version of NeurIPS 2021 paper. arXiv admin note: substantial text overlap with arXiv:2107.09282

Biased Stochastic First-Order Methods for Conditional Stochastic Optimization and Applications in Meta Learning

Yifan Hu, Siqi Zhang, Xin Chen, Niao He

Comments The updated version is the camera-ready version in NeurIPS 2020

Journal ref Advances in Neural Information Processing Systems 33 (NeurIPS 2020)

Riemannian Projection-free Online Learning

Zihao Hu, Guanghui Wang, Jacob Abernethy

Comments Published in Proceedings of The Thirty-seventh Annual Conference on Neural Information Processing Systems (NeurIPS 2023)

Generalized Semi-Supervised Learning via Self-Supervised Feature Adaptation

Jiachen Liang, Ruibing Hou, Hong Chang, Bingpeng Ma, Shiguang Shan, Xilin Chen

Comments 10 pages; Accepted by NeurIPS 2023

Zipper: A Multi-Tower Decoder Architecture for Fusing Modalities

Vicky Zayats, Peter Chen, Melissa Ferrari, Dirk Padfield

Comments Under review at NeurIPS

Multi-Prompt Alignment for Multi-Source Unsupervised Domain Adaptation

Haoran Chen, Xintong Han, Zuxuan Wu, Yu-Gang Jiang

Comments NeurIPS 2023 camera-ready version

May the Dance be with You: Dance Generation Framework for Non-Humanoids

Hyemin Ahn

Comments 13 pages, 6 Figures, Rejected at Neurips 2023

Recasting Continual Learning as Sequence Modeling

Soochan Lee, Jaehyeon Son, Gunhee Kim

Comments NeurIPS 2023

Unlocking the Potential of Renewable Energy Through Curtailment Prediction

Bilge Acun, Brent Morgan, Henry Richardson, Nat Steinsultz, Carole-Jean Wu

Comments The work was presented as a part of the Climate Change AI workshop at NeurIPS 2023

Gradient Descent with Polyak's Momentum Finds Flatter Minima via Large Catapults

Prin Phunyaphibarn, Junghyun Lee, Bohan Wang, Huishuai Zhang, Chulhee Yun

Comments v3: major updates; 25 pages, 17 figures; the first two authors contributed equally. The preliminary version was accepted to the NeurIPS 2023 M3L Workshop (oral) under the title "Large Catapults in Momentum Gradient Descent with Warmup: An Empirical Study."

Stochastic Collapse: How Gradient Noise Attracts SGD Dynamics Towards Simpler Subnetworks

Feng Chen, Daniel Kunin, Atsushi Yamamura, Surya Ganguli

Comments 37 pages, 12 figures, NeurIPS 2023

Gradient Descent Is Optimal Under Lower Restricted Secant Inequality And Upper Error Bound

Charles Guille-Escuret, Adam Ibrahim, Baptiste Goujaud, Ioannis Mitliagkas

Journal ref Advances in Neural Information Processing Systems 35 (2022): 24893-24904

Visualizing the loss landscape of Self-supervised Vision Transformer

Youngwan Lee, Jeffrey Ryan Willette, Jonghee Kim, Sung Ju Hwang

Comments NeurIPS 2023 Workshop: Self-Supervised Learning - Theory and Practice

Transition Path Sampling with Boltzmann Generator-based MCMC Moves

Michael Plainer, Hannes Stärk, Charlotte Bunne, Stephan Günnemann

Comments Spotlight at NeurIPS 2023 Generative AI and Biology Workshop

Scalable Video Object Segmentation with Identification Mechanism

Zongxin Yang, Jiaxu Miao, Yunchao Wei, Wenguan Wang, Xiaohan Wang, Yi Yang

Comments Accepted by TPAMI 2024. Extension of arXiv:2106.02638 (NeurIPS 2021)

Adapting to Continuous Covariate Shift via Online Density Ratio Estimation

Yu-Jie Zhang, Zhen-Yu Zhang, Peng Zhao, Masashi Sugiyama

Comments NeurIPS 2023

Adversarial Examples Might be Avoidable: The Role of Data Concentration in Adversarial Robustness

Ambar Pal, Jeremias Sulam, René Vidal

Comments Accepted to Neural Information Processing Systems (NeurIPS) 2023