NeurIPS

MCUFormer: Deploying Vision Transformers on Microcontrollers with Limited Memory

Yinan Liang, Ziwei Wang, Xiuwei Xu, Yansong Tang, Jie Zhou, Jiwen Lu

Comments Accepted by NeurIPS 2023

Finding Order in Chaos: A Novel Data Augmentation Method for Time Series in Contrastive Learning

Berken Utku Demirel, Christian Holz

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

LMC: Large Model Collaboration with Cross-assessment for Training-Free Open-Set Object Recognition

Haoxuan Qu, Xiaofei Hui, Yujun Cai, Jun Liu

Comments NeurIPS 2023

Hierarchical Open-vocabulary Universal Image Segmentation

Xudong Wang, Shufan Li, Konstantinos Kallidromitis, Yusuke Kato, Kazuki Kozuka, Trevor Darrell

Comments Project web-page: http://people.eecs.berkeley.edu/~xdwang/projects/HIPIE/; NeurIPS 2023 Camera-ready

ChessGPT: Bridging Policy Learning and Language Modeling

Xidong Feng, Yicheng Luo, Ziyan Wang, Hongrui Tang, Mengyue Yang, Kun Shao, David Mguni, Yali Du, Jun Wang

Comments Published as a conference article in NeurIPS 2023

Estimating Generic 3D Room Structures from 2D Annotations

Denys Rozumnyi, Stefan Popov, Kevis-Kokitsi Maninis, Matthias Nießner, Vittorio Ferrari

Comments https://github.com/google-research/cad-estate Accepted at 37th Conference on Neural Information Processing Systems (NeurIPS 2023) Track on Datasets and Benchmarks

Image Captioners Are Scalable Vision Learners Too

Michael Tschannen, Manoj Kumar, Andreas Steiner, Xiaohua Zhai, Neil Houlsby, Lucas Beyer

Comments Accepted at NeurIPS 2023. v2 adds SugarCrepe results and more ablations, v3 has minor fixes. v4 adds a code link ( https://github.com/google-research/big_vision ). v5 has minor fixes

One-Line-of-Code Data Mollification Improves Optimization of Likelihood-based Generative Models

Ba-Hien Tran, Giulio Franzese, Pietro Michiardi, Maurizio Filippone

Comments NeurIPS 2023

Unifying GANs and Score-Based Diffusion as Generative Particle Models

Jean-Yves Franceschi, Mike Gartrell, Ludovic Dos Santos, Thibaut Issenhuth, Emmanuel de Bézenac, Mickaël Chen, Alain Rakotomamonjy

Journal ref Thirty-seventh Conference on Neural Information Processing Systems, Neural Information Processing Systems Foundation, Dec. 2023, New Orleans, LA, USA

KSD Aggregated Goodness-of-fit Test

Antonin Schrab, Benjamin Guedj, Arthur Gretton

Comments 27 pages, 3 figures, Appendices A.4 and I.4 updated

Journal ref 36th Conference on Neural Information Processing Systems (NeurIPS 2022)

A 3D super-resolution of wind fields via physics-informed pixel-wise self-attention generative adversarial network

Takuya Kurihana, Kyongmin Yeo, Daniela Szwarcman, Bruce Elmegreen, Karthik Mukkavilli, Johannes Schmude, Levente Klein

Comments 7 pages, 4 figures, NeurIPS 2023 Workshop: Tackling Climate Change with Machine Learning

Covariance Adaptive Best Arm Identification

El Mehdi Saad, Gilles Blanchard, Nicolas Verzelen

Comments New version with some minor corrections

Journal ref Neurips 2023

MultiFusion: Fusing Pre-Trained Models for Multi-Lingual, Multi-Modal Image Generation

Marco Bellagente, Manuel Brack, Hannah Teufel, Felix Friedrich, Björn Deiseroth, Constantin Eichenberg, Andrew Dai, Robert Baldock, Souradeep Nanda, Koen Oostermeijer, Andres Felipe Cruz-Salinas, Patrick Schramowski, Kristian Kersting, Samuel Weinbach

Comments Proceedings of Advances in Neural Information Processing Systems: Annual Conference on Neural Information Processing Systems (NeurIPS)

Model-Based Control with Sparse Neural Dynamics

Ziang Liu, Genggeng Zhou, Jeff He, Tobia Marcucci, Li Fei-Fei, Jiajun Wu, Yunzhu Li

Comments Accepted at NeurIPS 2023. For tutorial code and additional visualizations, see https://robopil.github.io/Sparse-Dynamics/

Reducing Shape-Radiance Ambiguity in Radiance Fields with a Closed-Form Color Estimation Method

Qihang Fang, Yafei Song, Keqiang Li, Liefeng Bo

Comments This work has been published in NeurIPS 2023

Mini-GPTs: Efficient Large Language Models through Contextual Pruning

Tim Valicenti, Justice Vidal, Ritik Patnaik

Comments 7 pages, 4 figures, Neurips 2023 styling

Long-run Behaviour of Multi-fidelity Bayesian Optimisation

Gbetondji J-S Dovonon, Jakob Zeitler

Comments NeurIPS 2023 Workshop on Adaptive Experimental Design and Active Learning in the Real World

Hierarchical Vision Transformers for Context-Aware Prostate Cancer Grading in Whole Slide Images

Clément Grisi, Geert Litjens, Jeroen van der Laak

Comments Accepted at Medical Imaging meets NeurIPS 2023 workshop

Beyond Fairness: Alternative Moral Dimensions for Assessing Algorithms and Designing Systems

Kimi Wenzel, Geoff Kaufman, Laura Dabbish

Comments Presented at pluralism@CSCW workshop (Many Worlds of Ethics: Ethical Pluralism in CSCW) and M2@NeurIPS workshop (AI Meets Moral Philosophy and Moral Psychology: An Interdisciplinary Dialogue about Computational Ethics at NeurIPS) in 2023

Principled Weight Initialisation for Input-Convex Neural Networks

Pieter-Jan Hoedt, Günter Klambauer

Comments Presented at NeurIPS 2023

Bootstrapping Vision-Language Learning with Decoupled Language Pre-training

Yiren Jian, Chongyang Gao, Soroush Vosoughi

Comments Accepted to NeurIPS 2023 (spotlight). The code is available at https://github.com/yiren-jian/BLIText

Temporal Conditioning Spiking Latent Variable Models of the Neural Response to Natural Visual Scenes

Gehua Ma, Runhao Jiang, Rui Yan, Huajin Tang

Comments Accepted at NeurIPS 2023 (https://openreview.net/forum?id=V4YeOvsQfu). 22 pages, 7 figures, 3 tables

TransHP: Image Classification with Hierarchical Prompting

Wenhao Wang, Yifan Sun, Wei Li, Yi Yang

Comments Accepted to NeurIPS 2023; Released code

Debiasing Scores and Prompts of 2D Diffusion for View-consistent Text-to-3D Generation

Susung Hong, Donghoon Ahn, Seungryong Kim

Comments Accepted to NeurIPS 2023. Project Page: https://susunghong.github.io/Debiased-Score-Distillation-Sampling/

Transformed Low-Rank Parameterization Can Help Robust Generalization for Tensor Neural Networks

Andong Wang, Chao Li, Mingyuan Bai, Zhong Jin, Guoxu Zhou, Qibin Zhao

Comments 51 pages, presented on NeurIPS 2023

SegRefiner: Towards Model-Agnostic Segmentation Refinement with Discrete Diffusion Process

Mengyu Wang, Henghui Ding, Jun Hao Liew, Jiajun Liu, Yao Zhao, Yunchao Wei

Comments NeurIPS 2023, Code: https://github.com/MengyuWang826/SegRefiner

Diffusing More Objects for Semi-Supervised Domain Adaptation with Less Labeling

Leander van den Heuvel, Gertjan Burghouts, David W. Zhang, Gwenn Englebienne, Sabina B. van Rooij

Comments 4 pages, Workshop on DiffusionModels, NeurIPS 2023

Curriculum Learning for Cooperation in Multi-Agent Reinforcement Learning

Rupali Bhati, Sai Krishna Gottipati, Clodéric Mars, Matthew E. Taylor

Comments 9 pages, 5 figures. Presented at Agent Learning in Open-Endedness Workshop at Neural Information Processing Systems (NeurIPS 2023)

Squeezed Edge YOLO: Onboard Object Detection on Edge Devices

Edward Humes, Mozhgan Navardi, Tinoosh Mohsenin

Comments ML with New Compute Paradigms (MLNCP) Workshop at NeurIPS 2023

Smartpixels: Towards on-sensor inference of charged particle track parameters and uncertainties

Jennet Dickinson, Rachel Kovach-Fuentes, Lindsey Gray, Morris Swartz, Giuseppe Di Guglielmo, Alice Bean, Doug Berry, Manuel Blanco Valentin, Karri DiPetrillo, Farah Fahim, James Hirschauer, Shruti R. Kulkarni, Ron Lipton, Petar Maksimovic, Corrinne Mills, Mark S. Neubauer, Benjamin Parpillon, Gauri Pradhan, Chinar Syal, Nhan Tran, Dahai Wen, Jieun Yoo, Aaron Young

Comments 6 pages, 3 figures, submitted to Neural Information Processing Systems 2023 (NeurIPS)