NeurIPS

Transfer learning with affine model transformation

Shunya Minami, Kenji Fukumizu, Yoshihiro Hayashi, Ryo Yoshida

Comments 34 pages

Journal ref NeurIPS 2023

NeRF Revisited: Fixing Quadrature Instability in Volume Rendering

Mikaela Angelina Uy, Kiyohiro Nakayama, Guandao Yang, Rahul Krishna Thomas, Leonidas Guibas, Ke Li

Comments Neurips 2023

Pengi: An Audio Language Model for Audio Tasks

Soham Deshmukh, Benjamin Elizalde, Rita Singh, Huaming Wang

Comments Accepted at NeurIPS 2023. The manuscript is updated with additional experiments suggested by reviewers

Have it your way: Individualized Privacy Assignment for DP-SGD

Franziska Boenisch, Christopher Mühl, Adam Dziedzic, Roy Rinberg, Nicolas Papernot

Comments Published at NeurIPS'2024

Are you using test log-likelihood correctly?

Sameer K. Deshpande, Soumya Ghosh, Tin D. Nguyen, Tamara Broderick

Comments Presented at the ICBINB Workshop at NeurIPS 2022. This version accepted at TMLR, available at https://openreview.net/forum?id=n2YifD4Dxo

BasisFormer: Attention-based Time Series Forecasting with Learnable and Interpretable Basis

Zelin Ni, Hang Yu, Shizhan Liu, Jianguo Li, Weiyao Lin

Comments NeurIPS 2023(poster)

Learn to Categorize or Categorize to Learn? Self-Coding for Generalized Category Discovery

Sarah Rastegar, Hazel Doughty, Cees G. M. Snoek

Comments Accepted by NeurIPS 2023

Physics-Informed Calibration of Aeromagnetic Compensation in Magnetic Navigation Systems using Liquid Time-Constant Networks

Favour Nerrise, Andrew Sosa Sosanya, Patrick Neary

Comments Accepted at the NeurIPS 2023 Machine Learning and the Physical Sciences workshop, 7 pages, 4 figures, see code here: https://github.com/fnerrise/LNNs_MagNav/

Labeling Neural Representations with Inverse Recognition

Kirill Bykov, Laura Kopf, Shinichi Nakajima, Marius Kloft, Marina M. -C. Höhne

Comments 25 pages, 16 figures

Journal ref 37th Conference on Neural Information Processing Systems (NeurIPS 2023)

Generalized test utilities for long-tail performance in extreme multi-label classification

Erik Schultheis, Marek Wydmuch, Wojciech Kotłowski, Rohit Babbar, Krzysztof Dembczyński

Comments This is the authors' version of the work accepted to NeurIPS 2023; the final version of the paper, errors and typos corrected, and minor modifications to improve clarity

SpecTr: Fast Speculative Decoding via Optimal Transport

Ziteng Sun, Ananda Theertha Suresh, Jae Hun Ro, Ahmad Beirami, Himanshu Jain, Felix Yu

Comments NeurIPS 2023

Thought Cloning: Learning to Think while Acting by Imitating Human Thinking

Shengran Hu, Jeff Clune

Comments Accepted to NeurIPS 2023 as a spotlight

Training Neural Networks is NP-Hard in Fixed Dimension

Vincent Froese, Christoph Hertrich

Comments Paper accepted at NeurIPS 2023

Versatile Energy-Based Probabilistic Models for High Energy Physics

Taoli Cheng, Aaron Courville

Comments 17 pages, 9 figures. NeurIPS 2023 camera ready

POP-3D: Open-Vocabulary 3D Occupancy Prediction from Images

Antonin Vobecky, Oriane Siméoni, David Hurych, Spyros Gidaris, Andrei Bursuc, Patrick Pérez, Josef Sivic

Comments accepted to NeurIPS 2023

Residual Alignment: Uncovering the Mechanisms of Residual Networks

Jianing Li, Vardan Papyan

Comments Accepted at NeurIPS 2023 as a Poster paper

Concept Alignment

Sunayana Rane, Polyphony J. Bruna, Ilia Sucholutsky, Christopher Kello, Thomas L. Griffiths

Comments NeurIPS MP2 Workshop 2023

One-Step Diffusion Distillation via Deep Equilibrium Models

Zhengyang Geng, Ashwini Pokle, J. Zico Kolter

Comments NeurIPS 2023

CLadder: Assessing Causal Reasoning in Language Models

Zhijing Jin, Yuen Chen, Felix Leeb, Luigi Gresele, Ojasv Kamal, Zhiheng Lyu, Kevin Blin, Fernando Gonzalez Adauto, Max Kleiman-Weiner, Mrinmaya Sachan, Bernhard Schölkopf

Comments NeurIPS 2023; updated with CLadder dataset v1.5

Stanford-ORB: A Real-World 3D Object Inverse Rendering Benchmark

Zhengfei Kuang, Yunzhi Zhang, Hong-Xing Yu, Samir Agarwala, Shangzhe Wu, Jiajun Wu

Comments NeurIPS 2023 Datasets and Benchmarks Track. The first two authors contributed equally to this work. Project page: https://stanfordorb.github.io/

On the Relationship Between Relevance and Conflict in Online Social Link Recommendations

Yanbang Wang, Jon Kleinberg

Comments Accepted at NeurIPS 2023

Efficient Adaptation of Large Vision Transformer via Adapter Re-Composing

Wei Dong, Dawei Yan, Zhijun Lin, Peng Wang

Comments Paper is accepted to NeurIPS 2023

Last-Iterate Convergent Policy Gradient Primal-Dual Methods for Constrained MDPs

Dongsheng Ding, Chen-Yu Wei, Kaiqing Zhang, Alejandro Ribeiro

Comments 65 pages, 17 figures, and 1 table; NeurIPS 2023

Creating Multi-Level Skill Hierarchies in Reinforcement Learning

Joshua B. Evans, Özgür Şimşek

Comments 20 pages, 10 figures. Accepted at NeurIPS 2023

Causal Component Analysis

Liang Wendong, Armin Kekić, Julius von Kügelgen, Simon Buchholz, Michel Besserve, Luigi Gresele, Bernhard Schölkopf

Comments NeurIPS 2023 final camera-ready version

Diffusion-Based Adversarial Sample Generation for Improved Stealthiness and Controllability

Haotian Xue, Alexandre Araujo, Bin Hu, Yongxin Chen

Comments Accepted as a conference paper in NeurIPS'2023. Code repo: https://github.com/xavihart/Diff-PGD

Training Transitive and Commutative Multimodal Transformers with LoReTTa

Manuel Tran, Yashin Dicente Cid, Amal Lahiani, Fabian J. Theis, Tingying Peng, Eldad Klaiman

Comments Accepted at NeurIPS 2023 (poster). Camera-ready version

A Scalable Neural Network for DSIC Affine Maximizer Auction Design

Zhijian Duan, Haoran Sun, Yurong Chen, Xiaotie Deng

Comments NeurIPS 2023 (spotlight)

Augmenting Ground-Level PM2.5 Prediction via Kriging-Based Pseudo-Label Generation

Lei Duan, Ziyang Jiang, David Carlson

Comments 8 pages, 4 figures, NeurIPS 2023 Workshop: Tackling Climate Change with Machine Learning

Compute-Efficient Active Learning

Gábor Németh, Tamás Matuszka

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