ICLR

Set Learning for Accurate and Calibrated Models

Lukas Muttenthaler, Robert A. Vandermeulen, Qiuyi Zhang, Thomas Unterthiner, Klaus-Robert Müller

Comments Published as a conference paper at ICLR 2024

CoRe-GD: A Hierarchical Framework for Scalable Graph Visualization with GNNs

Florian Grötschla, Joël Mathys, Robert Veres, Roger Wattenhofer

Comments Published as a conference paper at ICLR 2024

Tool-Augmented Reward Modeling

Lei Li, Yekun Chai, Shuohuan Wang, Yu Sun, Hao Tian, Ningyu Zhang, Hua Wu

Comments ICLR 2024 Spotlight

ResFields: Residual Neural Fields for Spatiotemporal Signals

Marko Mihajlovic, Sergey Prokudin, Marc Pollefeys, Siyu Tang

Comments [ICLR 2024 Spotlight] Project and code at: https://markomih.github.io/ResFields/

On Penalty Methods for Nonconvex Bilevel Optimization and First-Order Stochastic Approximation

Jeongyeol Kwon, Dohyun Kwon, Stephen Wright, Robert Nowak

Comments ICLR 2024

KDSTM: Neural Semi-supervised Topic Modeling with Knowledge Distillation

Weijie Xu, Xiaoyu Jiang, Jay Desai, Bin Han, Fuqin Yan, Francis Iannacci

Comments 12 pages, 4 figures, ICLR 2022 Workshop

Journal ref ICLR 2022 Workshop PML4DC

Rethinking the Expressive Power of GNNs via Graph Biconnectivity

Bohang Zhang, Shengjie Luo, Liwei Wang, Di He

Comments Extended from ICLR 2023 Outstanding Paper; 60 pages, 12 figures. Fix typos in the previous version

Pushing Boundaries: Mixup's Influence on Neural Collapse

Quinn Fisher, Haoming Meng, Vardan Papyan

Comments Published as a conference paper at the International Conference on Learning Representations (ICLR 2024)

Large Language Model Cascades with Mixture of Thoughts Representations for Cost-efficient Reasoning

Murong Yue, Jie Zhao, Min Zhang, Liang Du, Ziyu Yao

Comments Accepted to ICLR 2024

CktGNN: Circuit Graph Neural Network for Electronic Design Automation

Zehao Dong, Weidong Cao, Muhan Zhang, Dacheng Tao, Yixin Chen, Xuan Zhang

Comments Accepted by ICLR (International Conference on Learning Representations) 2023

Universal Approximation Power of Deep Residual Neural Networks via Nonlinear Control Theory

Paulo Tabuada, Bahman Gharesifard

Comments Sejun Park and Geonho Hwang brought to our atention a mistake in the proof of Theorem 5.1. This mistake is corrected in this version with the consequence of increasing the number of neurons per layer from n+1 to 2n+1

Journal ref ICLR 2021, TAC 2023

Discovering Temporally-Aware Reinforcement Learning Algorithms

Matthew Thomas Jackson, Chris Lu, Louis Kirsch, Robert Tjarko Lange, Shimon Whiteson, Jakob Nicolaus Foerster

Comments Published at ICLR 2024

SoftEDA: Rethinking Rule-Based Data Augmentation with Soft Labels

Juhwan Choi, Kyohoon Jin, Junho Lee, Sangmin Song, Youngbin Kim

Comments ICLR 2023 Tiny Papers

It's Never Too Late: Fusing Acoustic Information into Large Language Models for Automatic Speech Recognition

Chen Chen, Ruizhe Li, Yuchen Hu, Sabato Marco Siniscalchi, Pin-Yu Chen, Ensiong Chng, Chao-Han Huck Yang

Comments Accepted to ICLR 2024, 17 pages. This work will be open sourced under MIT license

Task-customized Masked AutoEncoder via Mixture of Cluster-conditional Experts

Zhili Liu, Kai Chen, Jianhua Han, Lanqing Hong, Hang Xu, Zhenguo Li, James T. Kwok

Comments Accepted by ICLR 2023

Get What You Want, Not What You Don't: Image Content Suppression for Text-to-Image Diffusion Models

Senmao Li, Joost van de Weijer, Taihang Hu, Fahad Shahbaz Khan, Qibin Hou, Yaxing Wang, Jian Yang

Comments ICLR 2024. Our code is available in https://github.com/sen-mao/SuppressEOT

S2vNTM: Semi-supervised vMF Neural Topic Modeling

Weijie Xu, Jay Desai, Srinivasan Sengamedu, Xiaoyu Jiang, Francis Iannacci

Comments 17 pages, 9 figures, ICLR Workshop 2023. arXiv admin note: text overlap with arXiv:2307.01226

Journal ref ICLR Workshop 2023

Out-of-Variable Generalization for Discriminative Models

Siyuan Guo, Jonas Wildberger, Bernhard Schölkopf

Comments Accepted at ICLR 2024

LMUFormer: Low Complexity Yet Powerful Spiking Model With Legendre Memory Units

Zeyu Liu, Gourav Datta, Anni Li, Peter Anthony Beerel

Comments The 12th International Conference on Learning Representations (ICLR 2024)

How Realistic Is Your Synthetic Data? Constraining Deep Generative Models for Tabular Data

Mihaela Cătălina Stoian, Salijona Dyrmishi, Maxime Cordy, Thomas Lukasiewicz, Eleonora Giunchiglia

Comments Accepted at ICLR 2024

InstructScene: Instruction-Driven 3D Indoor Scene Synthesis with Semantic Graph Prior

Chenguo Lin, Yadong Mu

Comments Accepted by ICLR 2024 for spotlight presentation; Project page: https://chenguolin.github.io/projects/InstructScene

Noise Map Guidance: Inversion with Spatial Context for Real Image Editing

Hansam Cho, Jonghyun Lee, Seoung Bum Kim, Tae-Hyun Oh, Yonghyun Jeong

Comments ICLR 2024

Incentivized Truthful Communication for Federated Bandits

Zhepei Wei, Chuanhao Li, Tianze Ren, Haifeng Xu, Hongning Wang

Comments 20 pages, 2 figures. Accepted at ICLR 2024

AirPhyNet: Harnessing Physics-Guided Neural Networks for Air Quality Prediction

Kethmi Hirushini Hettige, Jiahao Ji, Shili Xiang, Cheng Long, Gao Cong, Jingyuan Wang

Comments Accepted by the 12th International Conference on Learning Representations (ICLR 2024)

Symbol: Generating Flexible Black-Box Optimizers through Symbolic Equation Learning

Jiacheng Chen, Zeyuan Ma, Hongshu Guo, Yining Ma, Jie Zhang, Yue-Jiao Gong

Comments Published as a conference paper at ICLR 2024

Imitation Learning from Observation with Automatic Discount Scheduling

Yuyang Liu, Weijun Dong, Yingdong Hu, Chuan Wen, Zhao-Heng Yin, Chongjie Zhang, Yang Gao

Comments Accepted by ICLR 2024

DFormer: Rethinking RGBD Representation Learning for Semantic Segmentation

Bowen Yin, Xuying Zhang, Zhongyu Li, Li Liu, Ming-Ming Cheng, Qibin Hou

Comments Accepted by ICLR 2024

General Neural Gauge Fields

Fangneng Zhan, Lingjie Liu, Adam Kortylewski, Christian Theobalt

Comments ICLR 2023

The Hedgehog & the Porcupine: Expressive Linear Attentions with Softmax Mimicry

Michael Zhang, Kush Bhatia, Hermann Kumbong, Christopher Ré

Comments 30 pages, 20 figures, 15 tables, ICLR 2024

A Hard-to-Beat Baseline for Training-free CLIP-based Adaptation

Zhengbo Wang, Jian Liang, Lijun Sheng, Ran He, Zilei Wang, Tieniu Tan

Comments Accepted by ICLR 2024