Chao Ma - RankMe

33 papers A* 11Journal 20Unranked 2

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	ARO: A New Lens On Matrix Optimization For Large Models. CoRR Wenbo Gong, Javier Zazo, Qijun Luo, Puqian Wang, James Hensman, Chao Ma
2025	J	`jnl`	Gradient Multi-Normalization for Stateless and Scalable LLM Training. CoRR Meyer Scetbon, Chao Ma, Wenbo Gong, Edward Meeds
2025	A*	`conf`	SWAN: SGD with Normalization and Whitening Enables Stateless LLM Training. ICML Chao Ma, Wenbo Gong, Meyer Scetbon, Edward Meeds
2025	J	`jnl`	Towards Efficient Optimizer Design for LLM via Structured Fisher Approximation with a Low-Rank Extension. CoRR Wenbo Gong, Meyer Scetbon, Chao Ma, Edward Meeds
2024	A*	`conf`	A Fixed-Point Approach for Causal Generative Modeling. ICML Meyer Scetbon, Joel Jennings, Agrin Hilmkil, Cheng Zhang, Chao Ma
2024	J	`jnl`	AVID: Adapting Video Diffusion Models to World Models. CoRR Marc Rigter, Tarun Gupta, Agrin Hilmkil, Chao Ma
2024	J	`jnl`	Deep End-to-end Causal Inference. Trans. Mach. Learn. Res. Tomas Geffner, Javier Antorán, Adam Foster, Wenbo Gong, Chao Ma, Emre Kiciman, Amit Sharma, Angus Lamb, Martin Kukla, Nick Pawlowski, Agrin Hilmkil, Joel Jennings, Meyer Scetbon, Miltiadis Allamanis, Cheng Zhang
2024	J	`jnl`	FiP: a Fixed-Point Approach for Causal Generative Modeling. CoRR Meyer Scetbon, Joel Jennings, Agrin Hilmkil, Cheng Zhang, Chao Ma
2024	J	`jnl`	SWAN: SGD with Normalization and Whitening Enables Stateless LLM Training. CoRR Chao Ma, Wenbo Gong, Meyer Scetbon, Edward Meeds
2024	J	`jnl`	The Essential Role of Causality in Foundation World Models for Embodied AI. CoRR Tarun Gupta, Wenbo Gong, Chao Ma, Nick Pawlowski, Agrin Hilmkil, Meyer Scetbon, Ade Famoti, Ashley Juan Llorens, Jianfeng Gao, Stefan Bauer, Danica Kragic, Bernhard Schölkopf, Cheng Zhang
2024	A*	`conf`	Towards Causal Foundation Model: on Duality between Optimal Balancing and Attention. ICML Jiaqi Zhang, Joel Jennings, Agrin Hilmkil, Nick Pawlowski, Cheng Zhang, Chao Ma
2023	A*	`conf`	Causal Reasoning in the Presence of Latent Confounders via Neural ADMG Learning. ICLR Matthew Ashman, Chao Ma, Agrin Hilmkil, Joel Jennings, Cheng Zhang
2023	J	`jnl`	Causal Reasoning in the Presence of Latent Confounders via Neural ADMG Learning. CoRR Matthew Ashman, Chao Ma, Agrin Hilmkil, Joel Jennings, Cheng Zhang
2023	J	`jnl`	Causal-Discovery Performance of ChatGPT in the context of Neuropathic Pain Diagnosis. CoRR Ruibo Tu, Chao Ma, Cheng Zhang
2023	—	`conf`	Research on cooperative UAV countermeasure strategy based on interception triangle. ICMLCA Shuyu Liu, Ting Chen, Tiantian Zhao, Shanshan Liu, Chao Ma
2023	J	`jnl`	Towards Causal Foundation Model: on Duality between Causal Inference and Attention. CoRR Jiaqi Zhang, Joel Jennings, Cheng Zhang, Chao Ma
2023	J	`jnl`	Understanding Causality with Large Language Models: Feasibility and Opportunities. CoRR Cheng Zhang, Stefan Bauer, Paul Bennett, Jiangfeng Gao, Wenbo Gong, Agrin Hilmkil, Joel Jennings, Chao Ma, Tom Minka, Nick Pawlowski, James Vaughan
2022	A*	`conf`	BSODA: A Bipartite Scalable Framework for Online Disease Diagnosis. WWW Weijie He, Xiaohao Mao, Chao Ma, Yu Huang, José Miguel Hernández-Lobato, Ting Chen
2022	J	`jnl`	Deep End-to-end Causal Inference. CoRR Tomas Geffner, Javier Antorán, Adam Foster, Wenbo Gong, Chao Ma, Emre Kiciman, Amit Sharma, Angus Lamb, Martin Kukla, Nick Pawlowski, Miltiadis Allamanis, Cheng Zhang
2022	A*	`conf`	Missing Data Imputation and Acquisition with Deep Hierarchical Models and Hamiltonian Monte Carlo. NeurIPS Ignacio Peis, Chao Ma, José Miguel Hernández-Lobato
2022	J	`jnl`	Missing Data Imputation and Acquisition with Deep Hierarchical Models and Hamiltonian Monte Carlo. CoRR Ignacio Peis, Chao Ma, José Miguel Hernández-Lobato
2021	A*	`conf`	Functional Variational Inference based on Stochastic Process Generators. NeurIPS Chao Ma, José Miguel Hernández-Lobato
2021	J	`jnl`	Identifiable Generative Models for Missing Not at Random Data Imputation. CoRR Chao Ma, Cheng Zhang
2021	A*	`conf`	Identifiable Generative models for Missing Not at Random Data Imputation. NeurIPS Chao Ma, Cheng Zhang
2020	J	`jnl`	Automatic Mapping of Landslides by the ResU-Net. Remote. Sens. Wenwen Qi, Mengfei Wei, Wentao Yang, Chong Xu, Chao Ma
2020	J	`jnl`	FIT: a Fast and Accurate Framework for Solving Medical Inquiring and Diagnosing Tasks. CoRR Weijie He, Xiaohao Mao, Chao Ma, José Miguel Hernández-Lobato, Ting Chen
2020	A*	`conf`	VAEM: a Deep Generative Model for Heterogeneous Mixed Type Data. NeurIPS Chao Ma, Sebastian Tschiatschek, Richard E. Turner, José Miguel Hernández-Lobato, Cheng Zhang
2020	J	`jnl`	VAEM: a Deep Generative Model for Heterogeneous Mixed Type Data. CoRR Chao Ma, Sebastian Tschiatschek, José Miguel Hernández-Lobato, Richard E. Turner, Cheng Zhang
2019	A*	`conf`	EDDI: Efficient Dynamic Discovery of High-Value Information with Partial VAE. ICML Chao Ma, Sebastian Tschiatschek, Konstantina Palla, José Miguel Hernández-Lobato, Sebastian Nowozin, Cheng Zhang
2019	—	`conf`	HM-VAEs: a Deep Generative Model for Real-valued Data with Heterogeneous Marginals. AABI Chao Ma, Sebastian Tschiatschek, Yingzhen Li, Richard E. Turner, José Miguel Hernández-Lobato, Cheng Zhang
2019	A*	`conf`	Variational Implicit Processes. ICML Chao Ma, Yingzhen Li, José Miguel Hernández-Lobato
2018	J	`jnl`	EDDI: Efficient Dynamic Discovery of High-Value Information with Partial VAE. CoRR Chao Ma, Sebastian Tschiatschek, Konstantina Palla, José Miguel Hernández-Lobato, Sebastian Nowozin, Cheng Zhang
2018	J	`jnl`	Variational Implicit Processes. CoRR Chao Ma, Yingzhen Li, José Miguel Hernández-Lobato