NeurIPS

Evaluating Self-Supervised Learning for Molecular Graph Embeddings

Hanchen Wang, Jean Kaddour, Shengchao Liu, Jian Tang, Joan Lasenby, Qi Liu

Comments Camera ready, NeurIPS Benchmark 2023

Thin and Deep Gaussian Processes

Daniel Augusto de Souza, Alexander Nikitin, ST John, Magnus Ross, Mauricio A. Álvarez, Marc Peter Deisenroth, João P. P. Gomes, Diego Mesquita, César Lincoln C. Mattos

Comments Accepted at the Conference on Neural Information Processing Systems (NeurIPS) 2023

Towards Generic Semi-Supervised Framework for Volumetric Medical Image Segmentation

Haonan Wang, Xiaomeng Li

Comments Accepted at NeurIPS 2023

Matrix Compression via Randomized Low Rank and Low Precision Factorization

Rajarshi Saha, Varun Srivastava, Mert Pilanci

Comments Accepted to the 37th Conference on Neural Information Processing Systems (NeurIPS 2023)

Fast and Simple Spectral Clustering in Theory and Practice

Peter Macgregor

Comments Accepted to NeurIPS'23

Regularization properties of adversarially-trained linear regression

Antônio H. Ribeiro, Dave Zachariah, Francis Bach, Thomas B. Schön

Comments Accepted (spotlight) NeurIPS 2023; A preliminary version of this work titled: "Surprises in adversarially-trained linear regression" was made available under a different identifier: arXiv:2205.12695

Wide Neural Networks as Gaussian Processes: Lessons from Deep Equilibrium Models

Tianxiang Gao, Xiaokai Huo, Hailiang Liu, Hongyang Gao

Comments Accepted by NeurIPS 2023

IDRNet: Intervention-Driven Relation Network for Semantic Segmentation

Zhenchao Jin, Xiaowei Hu, Lingting Zhu, Luchuan Song, Li Yuan, Lequan Yu

Comments Accepted by NeurIPs 2023

Reusing Pretrained Models by Multi-linear Operators for Efficient Training

Yu Pan, Ye Yuan, Yichun Yin, Zenglin Xu, Lifeng Shang, Xin Jiang, Qun Liu

Comments Accepted in NeurIPS 2023

Enhancing ML model accuracy for Digital VLSI circuits using diffusion models: A study on synthetic data generation

Prasha Srivastava, Pawan Kumar, Zia Abbas

Comments 7 pages, submitted to NeurIPS workshop 2023

Rotating Features for Object Discovery

Sindy Löwe, Phillip Lippe, Francesco Locatello, Max Welling

Comments Oral presentation at NeurIPS 2023

How many samples are needed to leverage smoothness?

Vivien Cabannes, Stefano Vigogna

Comments 34 pages, 13 figures

Journal ref NeurIPS 2023

Stable and low-precision training for large-scale vision-language models

Mitchell Wortsman, Tim Dettmers, Luke Zettlemoyer, Ari Morcos, Ali Farhadi, Ludwig Schmidt

Comments NeurIPS 2023

Graph Mixture of Experts: Learning on Large-Scale Graphs with Explicit Diversity Modeling

Haotao Wang, Ziyu Jiang, Yuning You, Yan Han, Gaowen Liu, Jayanth Srinivasa, Ramana Rao Kompella, Zhangyang Wang

Comments NeurIPS 2023

UniPC: A Unified Predictor-Corrector Framework for Fast Sampling of Diffusion Models

Wenliang Zhao, Lujia Bai, Yongming Rao, Jie Zhou, Jiwen Lu

Comments Accepted by NeurIPS 2023. Project page: https://unipc.ivg-research.xyz

Sketchy: Memory-efficient Adaptive Regularization with Frequent Directions

Vladimir Feinberg, Xinyi Chen, Y. Jennifer Sun, Rohan Anil, Elad Hazan

Comments 22 pages, 6 figures, 7 tables, NeurIPS 2023

False Discovery Proportion control for aggregated Knockoffs

Alexandre Blain, Bertrand Thirion, Olivier Grisel, Pierre Neuvial

Comments NeurIPS 2023

Repetition In Repetition Out: Towards Understanding Neural Text Degeneration from the Data Perspective

Huayang Li, Tian Lan, Zihao Fu, Deng Cai, Lemao Liu, Nigel Collier, Taro Watanabe, Yixuan Su

Comments Accepted to NeurIPS 2023

KAKURENBO: Adaptively Hiding Samples in Deep Neural Network Training

Truong Thao Nguyen, Balazs Gerofi, Edgar Josafat Martinez-Noriega, François Trahay, Mohamed Wahib

Comments Advances in Neural Information Processing Systems 2023 (NeurIPS 2023)

PAC Learning Linear Thresholds from Label Proportions

Anand Brahmbhatt, Rishi Saket, Aravindan Raghuveer

Comments Spotlight paper at Neural Information Processing Systems (NeurIPS), 2023

Beyond Normal: On the Evaluation of Mutual Information Estimators

Paweł Czyż, Frederic Grabowski, Julia E. Vogt, Niko Beerenwinkel, Alexander Marx

Comments Accepted at NeurIPS 2023. Code available at https://github.com/cbg-ethz/bmi

Sharp Bounds for Generalized Causal Sensitivity Analysis

Dennis Frauen, Valentyn Melnychuk, Stefan Feuerriegel

Comments Accepted at NeurIPS 2023

Bridging Discrete and Backpropagation: Straight-Through and Beyond

Liyuan Liu, Chengyu Dong, Xiaodong Liu, Bin Yu, Jianfeng Gao

Comments NeurIPS 2023 (Oral)

H2RBox-v2: Incorporating Symmetry for Boosting Horizontal Box Supervised Oriented Object Detection

Yi Yu, Xue Yang, Qingyun Li, Yue Zhou, Gefan Zhang, Feipeng Da, Junchi Yan

Comments 15 pages, 4 figures, 11 tables, accepted by NeurIPS'23, the source code is available at https://github.com/open-mmlab/mmrotate

AV-NeRF: Learning Neural Fields for Real-World Audio-Visual Scene Synthesis

Susan Liang, Chao Huang, Yapeng Tian, Anurag Kumar, Chenliang Xu

Comments NeurIPS 2023

Does Localization Inform Editing? Surprising Differences in Causality-Based Localization vs. Knowledge Editing in Language Models

Peter Hase, Mohit Bansal, Been Kim, Asma Ghandeharioun

Comments NeurIPS 2023 (Spotlight). 26 pages, 22 figures

Deep Learning for Global Wildfire Forecasting

Ioannis Prapas, Akanksha Ahuja, Spyros Kondylatos, Ilektra Karasante, Eleanna Panagiotou, Lazaro Alonso, Charalampos Davalas, Dimitrios Michail, Nuno Carvalhais, Ioannis Papoutsis

Comments Accepted at the NeurIPS 2022 workshop on Tackling Climate Change with Machine Learning. Version 2 has corrected the table of results (Table 1)

PUCA: Patch-Unshuffle and Channel Attention for Enhanced Self-Supervised Image Denoising

Hyemi Jang, Junsung Park, Dahuin Jung, Jaihyun Lew, Ho Bae, Sungroh Yoon

Comments Accepted to NeurIPS 2023

SoTTA: Robust Test-Time Adaptation on Noisy Data Streams

Taesik Gong, Yewon Kim, Taeckyung Lee, Sorn Chottananurak, Sung-Ju Lee

Comments Accepted to NeurIPS 2023

ZoomTrack: Target-aware Non-uniform Resizing for Efficient Visual Tracking

Yutong Kou, Jin Gao, Bing Li, Gang Wang, Weiming Hu, Yizheng Wang, Liang Li

Comments 19 pages, 7 figures, Accepted by NeurIPS 2023 as a Spotlight