Daniel Graves - RankMe

33 papers A* 6A 2C 1Misc 1Journal 19Unranked 3

Year	Rank	Type	Title / Venue / Authors
2022	J	`jnl`	Affordance as general value function: a computational model. Adapt. Behav. Daniel Graves, Johannes Günther, Jun Luo
2022	A*	`conf`	Offline Learning of Counterfactual Predictions for Real-World Robotic Reinforcement Learning. ICRA Jun Jin, Daniel Graves, Cameron Haigh, Jun Luo, Martin Jägersand
2022	A*	`conf`	What about Inputting Policy in Value Function: Policy Representation and Policy-Extended Value Function Approximator. AAAI Hongyao Tang, Zhaopeng Meng, Jianye Hao, Chen Chen, Daniel Graves, Dong Li, Changmin Yu, Hangyu Mao, Wulong Liu, Yaodong Yang, Wenyuan Tao, Li Wang
2021	A	`conf`	Diverse Auto-Curriculum is Critical for Successful Real-World Multiagent Learning Systems. AAMAS Yaodong Yang, Jun Luo, Ying Wen, Oliver Slumbers, Daniel Graves, Haitham Bou-Ammar, Jun Wang, Matthew E. Taylor
2021	J	`jnl`	Diverse Auto-Curriculum is Critical for Successful Real-World Multiagent Learning Systems. CoRR Yaodong Yang, Jun Luo, Ying Wen, Oliver Slumbers, Daniel Graves, Haitham Bou-Ammar, Jun Wang, Matthew E. Taylor
2021	A*	`conf`	Learning robust driving policies without online exploration. ICRA Daniel Graves, Nhat M. Nguyen, Kimia Hassanzadeh, Jun Jin, Jun Luo
2021	J	`jnl`	Learning robust driving policies without online exploration. CoRR Daniel Graves, Nhat M. Nguyen, Kimia Hassanzadeh, Jun Jin, Jun Luo
2020	J	`jnl`	Affordance as general value function: A computational model. CoRR Daniel Graves, Johannes Günther, Jun Luo
2020	A*	`conf`	Fixed-Horizon Temporal Difference Methods for Stable Reinforcement Learning. AAAI Kristopher De Asis, Alan Chan, Silviu Pitis, Richard S. Sutton, Daniel Graves
2020	J	`jnl`	LISPR: An Options Framework for Policy Reuse with Reinforcement Learning. CoRR Daniel Graves, Jun Jin, Jun Luo
2020	J	`jnl`	Learning predictive representations in autonomous driving to improve deep reinforcement learning. CoRR Daniel Graves, Nhat M. Nguyen, Kimia Hassanzadeh, Jun Jin
2020	A*	`conf`	Mapless Navigation among Dynamics with Social-safety-awareness: a reinforcement learning approach from 2D laser scans. ICRA Jun Jin, Nhat M. Nguyen, Nazmus Sakib, Daniel Graves, Hengshuai Yao, Martin Jägersand
2020	J	`jnl`	Offline Learning of Counterfactual Perception as Prediction for Real-World Robotic Reinforcement Learning. CoRR Jun Jin, Daniel Graves, Cameron Haigh, Jun Luo, Martin Jägersand
2020	J	`jnl`	Perception as prediction using general value functions in autonomous driving applications. CoRR Daniel Graves, Kasra Rezaee, Sean Scheideman
2020	Misc	`conf`	SMARTS: An Open-Source Scalable Multi-Agent RL Training School for Autonomous Driving. CoRL Ming Zhou, Jun Luo, Julian Villela, Yaodong Yang, David Rusu, Jiayu Miao, Weinan Zhang, Montgomery Alban, Iman Fadakar, Zheng Chen, Chongxi Huang, Ying Wen, Kimia Hassanzadeh, Daniel Graves, Zhengbang Zhu, Yihan Ni, Nhat M. Nguyen, Mohamed Elsayed, Haitham Ammar, Alexander I. Cowen-Rivers, Sanjeevan Ahilan, Zheng Tian, Daniel Palenicek, Kasra Rezaee, Peyman Yadmellat, Kun Shao, Dong Chen, Baokuan Zhang, Hongbo Zhang, Jianye Hao, Wulong Liu, Jun Wang
2020	J	`jnl`	SMARTS: Scalable Multi-Agent Reinforcement Learning Training School for Autonomous Driving. CoRR Ming Zhou, Jun Luo, Julian Villela, Yaodong Yang, David Rusu, Jiayu Miao, Weinan Zhang, Montgomery Alban, Iman Fadakar, Zheng Chen, Aurora Chongxi Huang, Ying Wen, Kimia Hassanzadeh, Daniel Graves, Dong Chen, Zhengbang Zhu, Nhat M. Nguyen, Mohamed Elsayed, Kun Shao, Sanjeevan Ahilan, Baokuan Zhang, Jiannan Wu, Zhengang Fu, Kasra Rezaee, Peyman Yadmellat, Mohsen Rohani, Nicolas Perez Nieves, Yihan Ni, Seyedershad Banijamali, Alexander I. Cowen-Rivers, Zheng Tian, Daniel Palenicek, Haitham Bou-Ammar, Hongbo Zhang, Wulong Liu, Jianye Hao, Jun Wang
2020	J	`jnl`	What About Taking Policy as Input of Value Function: Policy-extended Value Function Approximator. CoRR Hongyao Tang, Zhaopeng Meng, Jianye Hao, Chen Chen, Daniel Graves, Dong Li, Wulong Liu, Yaodong Yang
2019	J	`jnl`	Efficient decorrelation of features using Gramian in Reinforcement Learning. CoRR Borislav Mavrin, Daniel Graves, Alan Chan
2019	J	`jnl`	Fixed-Horizon Temporal Difference Methods for Stable Reinforcement Learning. CoRR Kristopher De Asis, Alan Chan, Silviu Pitis, Richard S. Sutton, Daniel Graves
2019	A*	`conf`	Importance Resampling for Off-policy Prediction. NeurIPS Matthew Schlegel, Wesley Chung, Daniel Graves, Jian Qian, Martha White
2019	J	`jnl`	Importance Resampling for Off-policy Prediction. CoRR Matthew Schlegel, Wesley Chung, Daniel Graves, Jian Qian, Martha White
2019	J	`jnl`	Mapless Navigation among Dynamics with Social-safety-awareness: a reinforcement learning approach from 2D laser scans. CoRR Jun Jin, Nhat M. Nguyen, Nazmus Sakib, Daniel Graves, Hengshuai Yao, Martin Jägersand
2019	A	`conf`	Perception as prediction using general value functions in autonomous driving applications. IROS Daniel Graves, Kasra Rezaee, Sean Scheideman
2019	J	`jnl`	Performance analysis and optimization for scalable deployment of deep learning models for country-scale settlement mapping on Titan supercomputer. Concurr. Comput. Pract. Exp. Kuldeep R. Kurte, Jibonananda Sanyal, Anne Berres, Dalton D. Lunga, Mark Coletti, Hsiuhan Lexie Yang, Daniel Graves, Benjamin Liebersohn, Amy N. Rose
2019	—	`conf`	Sequence Learning for Images Recognition in Videos with Differential Neural Networks. ICCI*CC Yingxu Wang, Omar A. Zatarain, Tony Tsai, Daniel Graves
2018	—	`conf`	A Survey and Formal Analyses on Sequence Learning Methodologies and Deep Neural Networks. ICCI*CC Yingxu Wang, Henry Leung, Marina L. Gavrilova, Omar A. Zatarain, Daniel Graves, Jianhua Lu, Newton Howard, Sam Kwong, Phillip C.-Y. Sheu, Shushma Patel
2014	J	`jnl`	A Clustering-Based Graph Laplacian Framework for Value Function Approximation in Reinforcement Learning. IEEE Trans. Cybern. Xin Xu, Zhenhua Huang, Daniel Graves, Witold Pedrycz
2012	J	`jnl`	Clustering with proximity knowledge and relational knowledge. Pattern Recognit. Daniel Graves, Joost Noppen, Witold Pedrycz
2010	J	`jnl`	Kernel-based fuzzy clustering and fuzzy clustering: A comparative experimental study. Fuzzy Sets Syst. Daniel Graves, Witold Pedrycz
2010	C	`conf`	Proximity fuzzy clustering and its application to time series clustering and prediction. ISDA Daniel Graves, Witold Pedrycz
2009	J	`jnl`	Fuzzy prediction architecture using recurrent neural networks. Neurocomputing Daniel Graves, Witold Pedrycz
2009	—	`conf`	Multivariate Segmentation of Time Series with Differential Evolution. IFSA/EUSFLAT Conf. Daniel Graves, Witold Pedrycz
2007	—	`ch.`	Fuzzy C-Means, Gustafson-Kessel FCM, and Kernel-Based FCM: A Comparative Study. Analysis and Design of Intelligent Systems using Soft Computing Techniques Daniel Graves, Witold Pedrycz