TMLR

Series of Hessian-Vector Products for Tractable Saddle-Free Newton Optimisation of Neural Networks

Elre T. Oldewage, Ross M. Clarke, José Miguel Hernández-Lobato

Comments 37 pages, 10 figures, 5 tables. To appear in TMLR. First two authors' order randomised

A VAE-based Framework for Learning Multi-Level Neural Granger-Causal Connectivity

Jiahe Lin, Huitian Lei, George Michailidis

Comments Accepted by Transactions on Machine Learning Research

DynaConF: Dynamic Forecasting of Non-Stationary Time Series

Siqi Liu, Andreas Lehrmann

Comments Accepted by Transactions on Machine Learning Research (TMLR), 2024

Size Lowerbounds for Deep Operator Networks

Anirbit Mukherjee, Amartya Roy

Comments 25 pages, 13 figures

Journal ref Published in Transactions on Machine Learning Research (TMLR) in February 2024

Training Language Models with Language Feedback at Scale

Jérémy Scheurer, Jon Ander Campos, Tomasz Korbak, Jun Shern Chan, Angelica Chen, Kyunghyun Cho, Ethan Perez

Comments Published in TMLR: https://openreview.net/forum?id=xo3hI5MwvU

Improving Code Generation by Training with Natural Language Feedback

Angelica Chen, Jérémy Scheurer, Tomasz Korbak, Jon Ander Campos, Jun Shern Chan, Samuel R. Bowman, Kyunghyun Cho, Ethan Perez

Comments Published in (and superceded by) TMLR: https://openreview.net/forum?id=xo3hI5MwvU

Exposing and Addressing Cross-Task Inconsistency in Unified Vision-Language Models

Adyasha Maharana, Amita Kamath, Christopher Clark, Mohit Bansal, Aniruddha Kembhavi

Comments TMLR 2024; Project Website: https://adymaharana.github.io/cococon/

Hierarchical Neural Simulation-Based Inference Over Event Ensembles

Lukas Heinrich, Siddharth Mishra-Sharma, Chris Pollard, Philipp Windischhofer

Comments 15+2 pages, 7 figures; v2, version published in TMLR

AutoML in the Age of Large Language Models: Current Challenges, Future Opportunities and Risks

Alexander Tornede, Difan Deng, Theresa Eimer, Joseph Giovanelli, Aditya Mohan, Tim Ruhkopf, Sarah Segel, Daphne Theodorakopoulos, Tanja Tornede, Henning Wachsmuth, Marius Lindauer

Comments Submitted and accepted at TMLR: https://openreview.net/forum?id=cAthubStyG

Automated Design of Metaheuristic Algorithms: A Survey

Qi Zhao, Qiqi Duan, Bai Yan, Shi Cheng, Yuhui Shi

Journal ref Transactions on Machine Learning Research, 2024, https://openreview.net/forum?id=qhtHsvF5zj

Leveraging Function Space Aggregation for Federated Learning at Scale

Nikita Dhawan, Nicole Mitchell, Zachary Charles, Zachary Garrett, Gintare Karolina Dziugaite

Comments 23 pages, 10 figures. Transactions on Machine Learning Research, 2024

Why should autoencoders work?

Matthew D. Kvalheim, Eduardo D. Sontag

Comments 24 pages, 9 figures; version 3 is accepted for publication in Transactions on Machine Learning Research (TMLR)

Accountable Textual-Visual Chat Learns to Reject Human Instructions in Image Re-creation

Zhiwei Zhang, Yuliang Liu

Comments TMLR, Survey Certification

Distributional GFlowNets with Quantile Flows

Dinghuai Zhang, Ling Pan, Ricky T. Q. Chen, Aaron Courville, Yoshua Bengio

Comments Accepted by TMLR

NorMatch: Matching Normalizing Flows with Discriminative Classifiers for Semi-Supervised Learning

Zhongying Deng, Rihuan Ke, Carola-Bibiane Schonlieb, Angelica I Aviles-Rivero

Comments Accepted to Transactions on Machine Learning Research

$f$-MICL: Understanding and Generalizing InfoNCE-based Contrastive Learning

Yiwei Lu, Guojun Zhang, Sun Sun, Hongyu Guo, Yaoliang Yu

Comments Accepted to TMLR in 2023

Break it, Imitate it, Fix it: Robustness by Generating Human-Like Attacks

Aradhana Sinha, Ananth Balashankar, Ahmad Beirami, Thi Avrahami, Jilin Chen, Alex Beutel

Journal ref Transactions on Machine Learning Research (2024)

Understanding the Role of Layer Normalization in Label-Skewed Federated Learning

Guojun Zhang, Mahdi Beitollahi, Alex Bie, Xi Chen

Comments accepted at TMLR

LLMs and the Abstraction and Reasoning Corpus: Successes, Failures, and the Importance of Object-based Representations

Yudong Xu, Wenhao Li, Pashootan Vaezipoor, Scott Sanner, Elias B. Khalil

Comments 26 pages, 15 figures, published in Transactions on Machine Learning Research (TMLR)

Indiscriminate Data Poisoning Attacks on Neural Networks

Yiwei Lu, Gautam Kamath, Yaoliang Yu

Comments Accepted to TMLR in 2022

Transfer Learning for Bayesian Optimization on Heterogeneous Search Spaces

Zhou Fan, Xinran Han, Zi Wang

Journal ref Transactions on Machine Learning Research (TMLR), February 2024

How does over-squashing affect the power of GNNs?

Francesco Di Giovanni, T. Konstantin Rusch, Michael M. Bronstein, Andreea Deac, Marc Lackenby, Siddhartha Mishra, Petar Veličković

Comments 36 pages; Published in Transactions on Machine Learning Research (TMLR)

Correlation Clustering with Active Learning of Pairwise Similarities

Linus Aronsson, Morteza Haghir Chehreghani

Journal ref Transactions on Machine Learning Research (TMLR) (2024). https://openreview.net/forum?id=Ryf1TVCjBz

MESSY Estimation: Maximum-Entropy based Stochastic and Symbolic densitY Estimation

Tony Tohme, Mohsen Sadr, Kamal Youcef-Toumi, Nicolas G. Hadjiconstantinou

Comments Published in Transactions on Machine Learning Research (TMLR)

Neural Circuit Diagrams: Robust Diagrams for the Communication, Implementation, and Analysis of Deep Learning Architectures

Vincent Abbott

Journal ref Transactions on Machine Learning Research (2024)

DDLP: Unsupervised Object-Centric Video Prediction with Deep Dynamic Latent Particles

Tal Daniel, Aviv Tamar

Comments TMLR 2024. Project site: https://taldatech.github.io/ddlp-web

Two Failures of Self-Consistency in the Multi-Step Reasoning of LLMs

Angelica Chen, Jason Phang, Alicia Parrish, Vishakh Padmakumar, Chen Zhao, Samuel R. Bowman, Kyunghyun Cho

Comments Accepted to TMLR: https://openreview.net/forum?id=5nBqY1y96B

Journal ref Transactions on Machine Learning Research (2024)

High-dimensional Bayesian Optimization via Covariance Matrix Adaptation Strategy

Lam Ngo, Huong Ha, Jeffrey Chan, Vu Nguyen, Hongyu Zhang

Comments 31 pages, 17 figures

Journal ref Transactions on Machine Learning Research 2024

Extending Path-Dependent NJ-ODEs to Noisy Observations and a Dependent Observation Framework

William Andersson, Jakob Heiss, Florian Krach, Josef Teichmann

Journal ref Transactions on Machine Learning Research (TMLR) 2024

Using Motion Cues to Supervise Single-Frame Body Pose and Shape Estimation in Low Data Regimes

Andrey Davydov, Alexey Sidnev, Artsiom Sanakoyeu, Yuhua Chen, Mathieu Salzmann, Pascal Fua

Comments 21 pages; TMLR