Papers
Causal Attribution Analysis for Continuous Outcomes
Shanshan Luo, Yu Yixuan, Chunchen Liu et al.
Causal Discovery from Conditionally Stationary Time Series
Carles Balsells-Rodas, Xavier Sumba, Tanmayee Narendra et al.
Causal Effect Identification in lvLiNGAM from Higher-Order Cumulants
Daniele Tramontano, Yaroslav Kivva, Saber Salehkaleybar et al.
Causal Invariance-aware Augmentation for Brain Graph Contrastive Learning
Minqi Yu, Jinduo Liu, Junzhong Ji
Causality-Aware Contrastive Learning for Robust Multivariate Time-Series Anomaly Detection
Hyungi Kim, Jisoo Mok, Dongjun Lee et al.
Causality Inspired Federated Learning for OOD Generalization
Jiayuan Zhang, Xuefeng Liu, Jianwei Niu et al.
Causal Logistic Bandits with Counterfactual Fairness Constraints
Jiajun Chen, Jin Tian, Christopher John Quinn
Causal-PIK: Causality-based Physical Reasoning with a Physics-Informed Kernel
Carlota Parés Morlans, Michelle Yi, Claire Chen et al.
Cavia: Camera-controllable Multi-view Video Diffusion with View-Integrated Attention
Dejia Xu, Yifan Jiang, Chen Huang et al.
CEGA: A Cost-Effective Approach for Graph-Based Model Extraction and Acquisition
Zebin Wang, Menghan Lin, Bolin Shen et al.
CellFlux: Simulating Cellular Morphology Changes via Flow Matching
Yuhui Zhang, Yuchang Su, Chenyu Wang et al.
Censor Dependent Variational Inference
Chuanhui Liu, Xiao Wang
CERTAIN: Context Uncertainty-aware One-Shot Adaptation for Context-based Offline Meta Reinforcement Learning
Hongtu Zhou, Ruiling Yang, Yakun Zhu et al.
Certifiably Robust Model Evaluation in Federated Learning under Meta-Distributional Shifts
Amir Najafi, Samin Mahdizadeh Sani, Farzan Farnia
Certification for Differentially Private Prediction in Gradient-Based Training
Matthew Robert Wicker, Philip Sosnin, Igor Shilov et al.
Certified Unlearning for Neural Networks
Anastasia Koloskova, Youssef Allouah, Animesh Jha et al.
CFP-Gen: Combinatorial Functional Protein Generation via Diffusion Language Models
Junbo Yin, Chao Zha, Wenjia He et al.
CFPT: Empowering Time Series Forecasting through Cross-Frequency Interaction and Periodic-Aware Timestamp Modeling
Feifei Kou, Jiahao Wang, Lei Shi et al.
Chameleon: A Flexible Data-mixing Framework for Language Model Pretraining and Finetuning
Wanyun Xie, Francesco Tonin, Volkan Cevher
Channel Normalization for Time Series Channel Identification
Seunghan Lee, Taeyoung Park, Kibok Lee
Chaos Meets Attention: Transformers for Large-Scale Dynamical Prediction
Yi He, Yiming Yang, Xiaoyuan Cheng et al.
CHATS: Combining Human-Aligned Optimization and Test-Time Sampling for Text-to-Image Generation
Minghao Fu, Guo-Hua Wang, Liangfu Cao et al.
Chip Placement with Diffusion Models
Vint Lee, Minh Nguyen, Leena Elzeiny et al.
Circumventing Backdoor Space via Weight Symmetry
Jie Peng, Hongwei Yang, Jing Zhao et al.
CLARIFY: Contrastive Preference Reinforcement Learning for Untangling Ambiguous Queries
Ni Mu, Hao Hu, Xiao Hu et al.