Papers
11,015 papers found
CoRTX: Contrastive Framework for Real-time Explanation
Yu-Neng Chuang, Guanchu Wang, Fan Yang et al.
Coupled Multiwavelet Operator Learning for Coupled Differential Equations
Xiongye Xiao, Defu Cao, Ruochen Yang et al.
Coverage-centric Coreset Selection for High Pruning Rates
Haizhong Zheng, Rui Liu, Fan Lai et al.
CrAM: A Compression-Aware Minimizer
Alexandra Peste, Adrian Vladu, Eldar Kurtic et al.
Critic Sequential Monte Carlo
Vasileios Lioutas, Jonathan Wilder Lavington, Justice Sefas et al.
CROM: Continuous Reduced-Order Modeling of PDEs Using Implicit Neural Representations
Peter Yichen Chen, Jinxu Xiang, Dong Heon Cho et al.
Cross-Layer Retrospective Retrieving via Layer Attention
Yanwen Fang, Yuxi CAI, Jintai Chen et al.
Cross-Level Distillation and Feature Denoising for Cross-Domain Few-Shot Classification
Hao ZHENG, Runqi Wang, Jianzhuang Liu et al.
CUDA: Curriculum of Data Augmentation for Long-tailed Recognition
Sumyeong Ahn, Jongwoo Ko, Se-Young Yun
Curriculum-based Co-design of Morphology and Control of Voxel-based Soft Robots
Yuxing Wang, Shuang Wu, Haobo Fu et al.
CUTS: Neural Causal Discovery from Irregular Time-Series Data
Yuxiao Cheng, Runzhao Yang, Tingxiong Xiao et al.
Cycle-consistent Masked AutoEncoder for Unsupervised Domain Generalization
Haiyang Yang, Xiaotong Li, SHIXIANG TANG et al.
Cycle to Clique (Cy2C) Graph Neural Network: A Sight to See beyond Neighborhood Aggregation
Yun Young Choi, Sun Woo Park, Youngho Woo et al.
D4AM: A General Denoising Framework for Downstream Acoustic Models
Chi-Chang Lee, Yu Tsao, Hsin-Min Wang et al.
D4FT: A Deep Learning Approach to Kohn-Sham Density Functional Theory
Tianbo Li, Min Lin, Zheyuan Hu et al.
DAG Learning on the Permutahedron
Valentina Zantedeschi, Luca Franceschi, Jean Kaddour et al.
DAG Matters! GFlowNets Enhanced Explainer for Graph Neural Networks
Wenqian Li, Yinchuan Li, Zhigang Li et al.
DamoFD: Digging into Backbone Design on Face Detection
Yang Liu, Jiankang Deng, Fei Wang et al.
DASHA: Distributed Nonconvex Optimization with Communication Compression and Optimal Oracle Complexity
Alexander Tyurin, Peter Richtárik
Data augmentation alone can improve adversarial training
Lin Li, Michael W. Spratling
Data Continuity Matters: Improving Sequence Modeling with Lipschitz Regularizer
Eric Qu, Xufang Luo, Dongsheng Li
Data-Free One-Shot Federated Learning Under Very High Statistical Heterogeneity
Clare Elizabeth Heinbaugh, Emilio Luz-Ricca, Huajie Shao
Dataless Knowledge Fusion by Merging Weights of Language Models
Xisen Jin, Xiang Ren, Daniel Preotiuc-Pietro et al.
Dataset Pruning: Reducing Training Data by Examining Generalization Influence
Shuo Yang, Zeke Xie, Hanyu Peng et al.