Most Cited ICLR "pollutant concentration forecasting" Papers

Three Mechanisms of Feature Learning in a Linear Network

Yizhou Xu, Liu Ziyin

Proximal Mapping Loss: Understanding Loss Functions in Crowd Counting & Localization

Wei LIN, Jia Wan, Antoni Chan

Adaptive Energy Alignment for Accelerating Test-Time Adaptation

Wonjeong Choi, Do-Yeon Kim, Jungwuk Park et al.

ADAM Optimization with Adaptive Batch Selection

Gyu Yeol Kim, Min-hwan Oh

Can Reinforcement Learning Solve Asymmetric Combinatorial-Continuous Zero-Sum Games?

TTVD: Towards a Geometric Framework for Test-Time Adaptation Based on Voronoi Diagram

Mingxi Lei, Chunwei Ma, Meng Ding et al.

Towards Empowerment Gain through Causal Structure Learning in Model-Based Reinforcement Learning

Hongye Cao, Fan Feng, Meng Fang et al.

Dynamic Assortment Selection and Pricing with Censored Preference Feedback

Jung-hun Kim, Min-hwan Oh

Causal Effect Estimation with Mixed Latent Confounders and Post-treatment Variables

Yaochen Zhu, Jing Ma, Liang Wu et al.

Sequential Stochastic Combinatorial Optimization Using Hierarchal Reinforcement Learning

Xinsong Feng, Zihan Yu, Yanhai Xiong et al.

Learning Regularized Graphon Mean-Field Games with Unknown Graphons

Fengzhuo Zhang, Vincent Tan, Zhaoran Wang et al.

Accelerated training through iterative gradient propagation along the residual path

Erwan Fagnou, Paul Caillon, Blaise Delattre et al.

TDDBench: A Benchmark for Training data detection

Zhihao Zhu, Yi Yang, Defu Lian

DyCAST: Learning Dynamic Causal Structure from Time Series

Yue Cheng, Bochen Lyu, Weiwei Xing et al.

New Algorithms for the Learning-Augmented k-means Problem

Junyu Huang, Qilong Feng, Ziyun Huang et al.

THE ROBUSTNESS OF DIFFERENTIABLE CAUSAL DISCOVERY IN MISSPECIFIED SCENARIOS

Huiyang Yi, Yanyan He, Duxin Chen et al.

Fitting Networks with a Cancellation Trick

Jiashun Jin, Jingming Wang

Learning a Fast Mixing Exogenous Block MDP using a Single Trajectory

Alexander Levine, Peter Stone, Amy Zhang

Efficient Policy Evaluation with Safety Constraint for Reinforcement Learning

Claire Chen, Shuze Liu, Shangtong Zhang

HADAMRNN: BINARY AND SPARSE TERNARY ORTHOGONAL RNNS

Armand Foucault, Francois Malgouyres, Franck Mamalet

High-Dynamic Radar Sequence Prediction for Weather Nowcasting Using Spatiotemporal Coherent Gaussian Representation

Ziye Wang, Yiran Qin, Lin Zeng et al.

Generalization and Distributed Learning of GFlowNets

Tiago Silva, Amauri Souza, Omar Rivasplata et al.

Privacy-Aware Lifelong Learning

Ozan Özdenizci, Elmar Rueckert, Robert Legenstein

Balanced Ranking with Relative Centrality: A multi-core periphery perspective

Chandra Sekhar Mukherjee, Jiapeng Zhang

Last Iterate Convergence of Incremental Methods as a Model of Forgetting

Xufeng Cai, Jelena Diakonikolas

Regret Bounds for Episodic Risk-Sensitive Linear Quadratic Regulator

Wenhao Xu, Xuefeng Gao, Xuedong He

Strength Estimation and Human-Like Strength Adjustment in Games

Chun Jung Chen, Chung-Chin Shih, Ti-Rong Wu

Inverse decision-making using neural amortized Bayesian actors

Dominik Straub, Tobias Fabian Niehues, Jan Peters et al.

Linear Mode Connectivity in Differentiable Tree Ensembles

Ryuichi Kanoh, Mahito Sugiyama

SGD with memory: fundamental properties and stochastic acceleration

Dmitry Yarotsky, Maksim Velikanov

Real-time design of architectural structures with differentiable mechanics and neural networks

Rafael Pastrana, Eder Medina, Isabel M. de Oliveira et al.

Scalable Decentralized Learning with Teleportation

Yuki Takezawa, Sebastian Stich

Scale-Free Graph-Language Models

Jianglin Lu, Yixuan Liu, Yitian Zhang et al.

EDiT: A Local-SGD-Based Efficient Distributed Training Method for Large Language Models

Jialiang Cheng, Ning Gao, Yun Yue et al.

Learning Successor Features with Distributed Hebbian Temporal Memory

Evgenii Dzhivelikian, Petr Kuderov, Aleksandr Panov

Decoupled Finetuning for Domain Generalizable Semantic Segmentation

Jaehyun Pahk, Donghyeon Kwon, Seong Joon Oh et al.

Node Similarities under Random Projections: Limits and Pathological Cases

Tvrtko Tadić, Cassiano O Becker, Jennifer Neville

Interactive Adjustment for Human Trajectory Prediction with Individual Feedback

Jianhua Sun, Yuxuan Li, Liang Chai et al.

Towards Explaining the Power of Constant-depth Graph Neural Networks for Structured Linear Programming

Qian Li, Minghui Ouyang, Tian Ding et al.

Execution-guided within-prompt search for programming-by-example

Gust Verbruggen, Ashish Tiwari, Mukul Singh et al.

Metric-Driven Attributions for Vision Transformers

Chase Walker, Sumit Jha, Rickard Ewetz

Centrality-guided Pre-training for Graph

Bin Liang, Shiwei Chen, Lin Gui et al.

ComLoRA: A Competitive Learning Approach for Enhancing LoRA

Qiushi Huang, Tom Ko, Lilian Tang et al.

Generalized Video Moment Retrieval

Qin You, Qilong Wu, Yicong Li et al.

L3Ms — Lagrange Large Language Models

Guneet Singh Dhillon, Xingjian Shi, Yee Whye Teh et al.

Elliptic Loss Regularization

Ali Hasan, Haoming Yang, Yuting Ng et al.

On the Importance of Language-driven Representation Learning for Heterogeneous Federated Learning

Yunlu Yan, Chun-Mei Feng, Wangmeng Zuo et al.

Pareto Prompt Optimization

Guang Zhao, Byung-Jun Yoon, Gilchan Park et al.

Minimal Impact ControlNet: Advancing Multi-ControlNet Integration

Shikun Sun, Min Zhou, Zixuan Wang et al.

Weighted Multi-Prompt Learning with Description-free Large Language Model Distillation

Sua Lee, Kyubum Shin, Jung Ho Park

Stochastic Bandits Robust to Adversarial Attacks

Xuchuang Wang, Maoli Liu, Jinhang Zuo et al.

Synergy and Diversity in CLIP: Enhancing Performance Through Adaptive Backbone Ensembling

Cristian Rodriguez-Opazo, Ehsan Abbasnejad, Damien Teney et al.

Union-over-Intersections: Object Detection beyond Winner-Takes-All

Aritra Bhowmik, Pascal Mettes, Martin R. Oswald et al.

Improving Convergence Guarantees of Random Subspace Second-order Algorithm for Nonconvex Optimization

Rei Higuchi, Pierre-Louis Poirion, Akiko Takeda

Minimax Optimal Reinforcement Learning with Quasi-Optimism

Harin Lee, Min-hwan Oh

Improved Algorithms for Kernel Matrix-Vector Multiplication Under Sparsity Assumptions

Piotr Indyk, Michael Kapralov, Kshiteej Jitesh Sheth et al.

Exploring channel distinguishability in local neighborhoods of the model space in quantum neural networks

Sabrina Herbst, Sandeep Cranganore, Vincenzo De Maio et al.

ToddlerDiffusion: Interactive Structured Image Generation with Cascaded Schrödinger Bridge

Eslam Abdelrahman, Liangbing Zhao, Tao Hu et al.

Which Tasks Should Be Compressed Together? A Causal Discovery Approach for Efficient Multi-Task Representation Compression

Sha Guo, Jing Chen, Zixuan Hu et al.

High-Quality Joint Image and Video Tokenization with Causal VAE

Dawit Mureja Argaw, Xian Liu, Qinsheng Zhang et al.

InstaTrain: Adaptive Training via Ultra-Fast Natural Annealing within Dynamical Systems

Chuan Liu, Ruibing Song, Chunshu Wu et al.

ELBOing Stein: Variational Bayes with Stein Mixture Inference

Ola Rønning, Eric Nalisnick, Christophe Ley et al.

SaRA: High-Efficient Diffusion Model Fine-tuning with Progressive Sparse Low-Rank Adaptation

Teng Hu, Jiangning Zhang, Ran Yi et al.

Beyond Random Augmentations: Pretraining with Hard Views

Fabio Ferreira, Ivo Rapant, Jörg Franke et al.

InversionGNN: A Dual Path Network for Multi-Property Molecular Optimization

Yifan Niu, Ziqi Gao, Tingyang Xu et al.

Filtered not Mixed: Filtering-Based Online Gating for Mixture of Large Language Models

Raeid Saqur, Anastasis Kratsios, Florian Krach et al.

Probabilistic Neural Pruning via Sparsity Evolutionary Fokker-Planck-Kolmogorov Equation

Zhanfeng Mo, Haosen Shi, Sinno Jialin Pan

Revisiting text-to-image evaluation with Gecko: on metrics, prompts, and human rating

Olivia Wiles, Chuhan Zhang, Isabela Albuquerque et al.

Adversarial Training for Defense Against Label Poisoning Attacks

Melis Ilayda Bal, Volkan Cevher, Michael Muehlebach

Certified Robustness Under Bounded Levenshtein Distance

Elias Abad Rocamora, Grigorios Chrysos, Volkan Cevher

Multi-agent cooperation through learning-aware policy gradients

Alexander Meulemans, Seijin Kobayashi, Johannes von Oswald et al.

Field-DiT: Diffusion Transformer on Unified Video, 3D, and Game Field Generation

Kangfu Mei, Mo Zhou, Vishal Patel

From Tokens to Lattices: Emergent Lattice Structures in Language Models

Bo Xiong, Steffen Staab

The Computational Complexity of Positive Non-Clashing Teaching in Graphs

Robert Ganian, Liana Khazaliya, Fionn Mc Inerney et al.

ADMM for Structured Fractional Minimization

Ganzhao Yuan

ReCogLab: a framework testing relational reasoning & cognitive hypotheses on LLMs

Andrew Liu, Henry Prior, Gargi Balasubramaniam et al.

Exploring Learning Complexity for Efficient Downstream Dataset Pruning

Wenyu Jiang, Zhenlong Liu, Zejian Xie et al.

DLEFT-MKC: Dynamic Late Fusion Multiple Kernel Clustering with Robust Tensor Learning via Min-Max Optimization

Yi Zhang, Siwei Wang, Jiyuan Liu et al.

Analyzing Neural Scaling Laws in Two-Layer Networks with Power-Law Data Spectra

Roman Worschech, Bernd Rosenow

Learning Structured Representations by Embedding Class Hierarchy with Fast Optimal Transport

Siqi Zeng, Sixian Du, Makoto Yamada et al.

Input Space Mode Connectivity in Deep Neural Networks

Jakub Vrabel, Ori Shem-ur, Yaron Oz et al.

Gaussian Differentially Private Human Faces Under a Face Radial Curve Representation

Carlos Soto, Matthew Reimherr, Aleksandra Slavkovic et al.

What Do You See in Common? Learning Hierarchical Prototypes over Tree-of-Life to Discover Evolutionary Traits

Harish Babu Manogaran, M. Maruf, Arka Daw et al.

PseDet: Revisiting the Power of Pseudo Label in Incremental Object Detection

Qiuchen Wang, Zehui Chen, Chenhongyi Yang et al.

How Gradient descent balances features: A dynamical analysis for two-layer neural networks

Zhenyu Zhu, Fanghui Liu, Volkan Cevher

CR2PQ: Continuous Relative Rotary Positional Query for Dense Visual Representation Learning

Shaofeng Zhang, Qiang Zhou, Sitong Wu et al.

FACTS: A Factored State-Space Framework for World Modelling

Li Nanbo, Firas Laakom, Yucheng XU et al.

Self-supervised Monocular Depth Estimation Robust to Reflective Surface Leveraged by Triplet Mining

Wonhyeok Choi, Kyumin Hwang, Wei Peng et al.

GPromptShield: Elevating Resilience in Graph Prompt Tuning Against Adversarial Attacks

Shuhan Song, Ping Li, Ming Dun et al.

MuseGNN: Forming Scalable, Convergent GNN Layers that Minimize a Sampling-Based Energy

Haitian Jiang, Renjie Liu, Zengfeng Huang et al.

Generalizing Weisfeiler-Lehman Kernels to Subgraphs

Dongkwan Kim, Alice Oh

LocoVR: Multiuser Indoor Locomotion Dataset in Virtual Reality

Kojiro Takeyama, Yimeng Liu, Misha Sra

PT-T2I/V: An Efficient Proxy-Tokenized Diffusion Transformer for Text-to-Image/Video-Task

Jing Wang, Ao Ma, Jiasong Feng et al.

Aligning Generative Denoising with Discriminative Objectives Unleashes Diffusion for Visual Perception

Ziqi Pang, Xin Xu, Yu-Xiong Wang

Associative memory and dead neurons

Vladimir Fanaskov, Ivan Oseledets

RESfM: Robust Deep Equivariant Structure from Motion

Fadi Khatib, Yoni Kasten, Dror Moran et al.

Democratic Training Against Universal Adversarial Perturbations

Bing Sun, Jun Sun, Wei Zhao

Conservative Contextual Bandits: Beyond Linear Representations

Rohan Deb, Mohammad Ghavamzadeh, Arindam Banerjee

Robust Model Based Reinforcement Learning Using $\mathcal{L}_1$ Adaptive Control

Minjun Sung, Sambhu Harimanas Karumanchi, Aditya Gahlawat et al.

Pooling Image Datasets with Multiple Covariate Shift and Imbalance

Sotirios Panagiotis Chytas, Vishnu Lokhande, Vikas Singh

Leveraging Uncertainty Estimates To Improve Classifier Performance

Gundeep Arora, Srujana Merugu, Anoop Saladi et al.

Rethinking and Extending the Probabilistic Inference Capacity of GNNs

Tuo Xu, Lei Zou

Understanding the Robustness of Randomized Feature Defense Against Query-Based Adversarial Attacks

Hung Quang Nguyen, Yingjie Lao, Tung Pham et al.

Achieving Sample and Computational Efficient Reinforcement Learning by Action Space Reduction via Grouping

Yining Li, Peizhong Ju, Ness Shroff

Selective Mixup Fine-Tuning for Optimizing Non-Decomposable Objectives

Shrinivas Ramasubramanian, Harsh Rangwani, Sho Takemori et al.

NfgTransformer: Equivariant Representation Learning for Normal-form Games

SIQI LIU, Luke Marris, Georgios Piliouras et al.

Bayesian Bi-clustering of Neural Spiking Activity with Latent Structures

Ganchao Wei

A representation-learning game for classes of prediction tasks

Neria Uzan, Nir Weinberger

Graph Generation with $K^2$-trees

Yunhui Jang, Dongwoo Kim, Sungsoo Ahn

RAPPER: Reinforced Rationale-Prompted Paradigm for Natural Language Explanation in Visual Question Answering

Kai-Po Chang, Chi-Pin Huang, Wei-Yuan Cheng et al.

Diagnosing Transformers: Illuminating Feature Spaces for Clinical Decision-Making

Aliyah Hsu, Yeshwanth Cherapanamjeri, Briton Park et al.

Flat Minima in Linear Estimation and an Extended Gauss Markov Theorem

Simon Segert

Attention-based Iterative Decomposition for Tensor Product Representation

Taewon Park, inchul choi, Minho Lee

Improved Diffusion-based Generative Model with Better Adversarial Robustness

Zekun Wang, Mingyang Yi, Shuchen Xue et al.

SINGER: Stochastic Network Graph Evolving Operator for High Dimensional PDEs

Mingquan Feng, Yixin Huang, Weixin Liao et al.

Efficient Causal Decision Making with One-sided Feedback

Jianing Chu, Shu Yang, Wenbin Lu et al.

Discrete Latent Plans via Semantic Skill Abstractions

Haobin Jiang, Wang, Zongqing Lu

R2Det: Exploring Relaxed Rotation Equivariance in 2D Object Detection

Zhiqiang Wu, Yingjie Liu, Hanlin Dong et al.

Local Steps Speed Up Local GD for Heterogeneous Distributed Logistic Regression

Michael Crawshaw, Blake Woodworth, Mingrui Liu

SparsyFed: Sparse Adaptive Federated Learning

Adriano Guastella, Lorenzo Sani, Alex Iacob et al.

How Learnable Grids Recover Fine Detail in Low Dimensions: A Neural Tangent Kernel Analysis of Multigrid Parametric Encodings

Samuel Audia, Soheil Feizi, Matthias Zwicker et al.

Boosting Perturbed Gradient Ascent for Last-Iterate Convergence in Games

Kenshi Abe, Mitsuki Sakamoto, Kaito Ariu et al.

Graph Neural Networks Gone Hogwild

Olga Solodova, Nick Richardson, Deniz Oktay et al.

Durable Quantization Conditioned Misalignment Attack on Large Language Models

Peiran Dong, Haowei Li, Song Guo

Rethinking Self-Distillation: Label Averaging and Enhanced Soft Label Refinement with Partial Labels

Hyeonsu Jeong, Hye Won Chung

Minimax Optimal Two-Stage Algorithm For Moment Estimation Under Covariate Shift

Zhen Zhang, Xin Liu, Shaoli Wang et al.

Locally Connected Echo State Networks for Time Series Forecasting

Filip Matzner, František Mráz

Clique Number Estimation via Differentiable Functions of Adjacency Matrix Permutations

Indradyumna Roy, Eeshaan Jain, Soumen Chakrabarti et al.

Separation Power of Equivariant Neural Networks

Marco Pacini, Xiaowen Dong, Bruno Lepri et al.

When GNNs meet symmetry in ILPs: an orbit-based feature augmentation approach

Qian Chen, Lei Li, Qian Li et al.

Generative Adversarial Ranking Nets

Yinghua Yao, Yuangang Pan, Jing Li et al.

Controlled LLM Decoding via Discrete Auto-regressive Biasing

Patrick Pynadath, Ruqi Zhang

SFESS: Score Function Estimators for $k$-Subset Sampling

Klas Wijk, Ricardo Vinuesa, Hossein Azizpour

Gaussian Splatting Lucas-Kanade

Liuyue Xie, Joel Julin, Koichiro Niinuma et al.

A Large-scale Training Paradigm for Graph Generative Models

Yu Wang, Ryan Rossi, Namyong Park et al.

Beyond single neurons: population response geometry in digital twins of mouse visual cortex

Dario Liscai, Emanuele Luconi, Alessandro Marin Vargas et al.

Scale-aware Recognition in Satellite Images under Resource Constraints

Shreelekha Revankar, Cheng Perng Phoo, Utkarsh Kumar Mall et al.

Event-Driven Online Vertical Federated Learning

Ganyu Wang, Boyu Wang, Bin Gu et al.

DynAlign: Unsupervised Dynamic Taxonomy Alignment for Cross-Domain Segmentation

HAN SUN, Rui Gong, Ismail Nejjar et al.

Collapsed Language Models Promote Fairness

Jingxuan Xu, Wuyang Chen, Linyi Li et al.

Long-Context Linear System Identification

Oğuz Kaan Yüksel, Mathieu Even, Nicolas Flammarion

Learning Randomized Algorithms with Transformers

Johannes von Oswald, Seijin Kobayashi, Yassir Akram et al.

VOILA: Evaluation of MLLMs For Perceptual Understanding and Analogical Reasoning

Nilay Yilmaz, Maitreya Patel, Lawrence Luo et al.

LevAttention: Time, Space and Streaming Efficient Algorithm for Heavy Attentions

Ravindran Kannan, Chiranjib Bhattacharyya, Praneeth Kacham et al.

On the Almost Sure Convergence of the Stochastic Three Points Algorithm

Taha EL BAKKALI EL KADI, Omar Saadi

Normed Spaces for Graph Embedding

Wei Zhao, Diaaeldin Taha, J. Riestenberg et al.

Safety Representations for Safer Policy Learning

Kaustubh Mani, Vincent Mai, Charlie Gauthier et al.

Policy Gradient with Kernel Quadrature

Tetsuro Morimura, Satoshi Hayakawa

MGCFNN: A Neural MultiGrid Solver with Novel Fourier Neural Network for High Wave Number Helmholtz Equations

Yan Xie, Minrui Lv, Chen-Song Zhang

qNBO: quasi-Newton Meets Bilevel Optimization

Sheng Fang, Yongjin Liu, Wei Yao et al.

Injective flows for star-like manifolds

Marcello Negri, Jonathan Aellen, Volker Roth

Finally Rank-Breaking Conquers MNL Bandits: Optimal and Efficient Algorithms for MNL Assortment

Aadirupa Saha, Pierre Gaillard

On the Adversarial Vulnerability of Label-Free Test-Time Adaptation

Shahriar Rifat, Jonathan Ashdown, Michael De Lucia et al.

Long-tailed Adversarial Training with Self-Distillation

Seungju Cho, Hongsin Lee, Changick Kim

GeoILP: A Synthetic Dataset to Guide Large-Scale Rule Induction

Si Chen, Richong Zhang, Xu Zhang

EvA: Erasing Spurious Correlations with Activations

Qiyuan He, Kai Xu, Angela Yao

Distribution Backtracking Builds A Faster Convergence Trajectory for Diffusion Distillation

Shengyuan Zhang, Ling Yang, Zejian Li et al.

Satisficing Regret Minimization in Bandits

Qing Feng, Tianyi Ma, Ruihao Zhu

Going Beyond Static: Understanding Shifts with Time-Series Attribution

Jiashuo Liu, Nabeel Seedat, Peng Cui et al.

PIED: Physics-Informed Experimental Design for Inverse Problems

Apivich Hemachandra, Gregory Kang Ruey Lau, See-Kiong Ng et al.

DistillHGNN: A Knowledge Distillation Approach for High-Speed Hypergraph Neural Networks

Saman Forouzandeh, Parham Moradi Dowlatabadi, Mahdi Jalili

Binary Losses for Density Ratio Estimation

Werner Zellinger

Learning under Temporal Label Noise

Sujay Nagaraj, Walter Gerych, Sana Tonekaboni et al.

CLDyB: Towards Dynamic Benchmarking for Continual Learning with Pre-trained Models

Shengzhuang Chen, Yikai Liao, Xiaoxiao Sun et al.

A Robust Method to Discover Causal or Anticausal Relation

Yu Yao, Yang Zhou, Bo Han et al.

DUET: Decentralized Bilevel Optimization without Lower-Level Strong Convexity

Zhen Qin, Zhuqing Liu, Songtao Lu et al.

Complementary Label Learning with Positive Label Guessing and Negative Label Enhancement

Yuhang Li, Zhuying Li, Yuheng Jia

Unhackable Temporal Reward for Scalable Video MLLMs

En Yu, Kangheng Lin, Liang Zhao et al.

Debiasing Federated Learning with Correlated Client Participation

Zhenyu Sun, Ziyang Zhang, Zheng Xu et al.

Unsupervised Disentanglement of Content and Style via Variance-Invariance Constraints

Yuxuan Wu, Ziyu Wang, Bhiksha Raj et al.

Neural networks on Symmetric Spaces of Noncompact Type

Xuan Son Nguyen, Yang, Aymeric Histace

LEAD: Min-Max Optimization from a Physical Perspective

Guillaume Lajoie, Amartya Mitra, Reyhane Askari Hemmat et al.

LiFT: Learning to Fine-Tune via Bayesian Parameter Efficient Meta Fine-Tuning

Minyoung Kim, Timothy Hospedales

Revisiting Large-Scale Non-convex Distributionally Robust Optimization

Qi Zhang, Yi Zhou, Simon Khan et al.

Dynamic Contrastive Skill Learning with State-Transition Based Skill Clustering and Dynamic Length Adjustment

Jinwoo Choi, Seung-Woo Seo

3DIS: Depth-Driven Decoupled Image Synthesis for Universal Multi-Instance Generation

Dewei Zhou, Ji Xie, Zongxin Yang et al.

Risk-Sensitive Variational Actor-Critic: A Model-Based Approach

Alonso Granados, Mohammadreza Ebrahimi, Jason Pacheco

Training Large Language Models for Retrieval-Augmented Question Answering through Backtracking Correction

Huawen Feng, ZekunYao, Junhao Zheng et al.

Bandit Learning in Matching Markets with Indifference

Fang Kong, Jingqi Tang, Mingzhu Li et al.

Learning Gain Map for Inverse Tone Mapping

yinuo liao, Yuanshen Guan, Ruikang Xu et al.

Fast and Accurate Blind Flexible Docking

Zizhuo Zhang, Lijun Wu, Kaiyuan Gao et al.

Learning Neural Networks with Distribution Shift: Efficiently Certifiable Guarantees

Gautam Chandrasekaran, Adam Klivans, Lin Lin Lee et al.

A Large-scale Dataset and Benchmark for Commuting Origin-Destination Flow Generation

Can Rong, Jingtao Ding, Yan Liu et al.

Utilitarian Algorithm Configuration for Infinite Parameter Spaces

Devon Graham, Kevin Leyton-Brown

Feedback Schrödinger Bridge Matching

Panagiotis Theodoropoulos, Nikolaos Komianos, Vincent Pacelli et al.

Improving Graph Neural Networks by Learning Continuous Edge Directions

Seong Ho Pahng, Sahand Hormoz

Learning Robust Representations with Long-Term Information for Generalization in Visual Reinforcement Learning

Rui Yang, Jie Wang, Qijie Peng et al.

ConcreTizer: Model Inversion Attack via Occupancy Classification and Dispersion Control for 3D Point Cloud Restoration

Youngseok Kim, Sunwook Hwang, Hyung-Sin Kim et al.

Zero-cost Proxy for Adversarial Robustness Evaluation

Yuqi Feng, Yuwei Ou, Jiahao Fan et al.

Optimal Learning of Kernel Logistic Regression for Complex Classification Scenarios

Hongwei Wen, Annika Betken, Hanyuan Hang

Systems with Switching Causal Relations: A Meta-Causal Perspective

Moritz Willig, Tim Tobiasch, Florian Busch et al.

Towards Scalable Topological Regularizers

Wong Hiu-Tung, Darrick Lee, Hong Yan

Schur's Positive-Definite Network: Deep Learning in the SPD cone with structure

Can Pouliquen, Mathurin Massias, Titouan Vayer

Optimizing 4D Gaussians for Dynamic Scene Video from Single Landscape Images

In-Hwan Jin, Haesoo Choo, Seong-Hun Jeong et al.

Generating Less Certain Adversarial Examples Improves Robust Generalization

Minxing Zhang, Michael Backes, Xiao Zhang

SWEb: A Large Web Dataset for the Scandinavian Languages

Tobias Norlund, Tim Isbister, Amaru Cuba Gyllensten et al.

Data Distillation for extrapolative protein design through exact preference optimization

Mostafa Karimi, Sharmi Banerjee, Tommi Jaakkola et al.

Efficient and Trustworthy Causal Discovery with Latent Variables and Complex Relations

Xiuchuan Li, Tongliang Liu

NRGBoost: Energy-Based Generative Boosted Trees

João Bravo

On Rollouts in Model-Based Reinforcement Learning

Bernd Frauenknecht, Devdutt Subhasish, Friedrich Solowjow et al.