Cryptocurrency Portfolio Management with Deep Reinforcement Learning. - Zhengyao Jiang; Jinjun Liang (CoRR, 2016)

A Deep Reinforcement Learning Framework for the Financial Portfolio Management Problem. - Zhengyao Jiang; Dixing Xu; Jinjun Liang (CoRR, 2017)

Neural Logic Reinforcement Learning. - Zhengyao Jiang; Shan Luo (ICML, 2019)

Grid-to-Graph: Flexible Spatial Relational Inductive Biases for Reinforcement Learning. - Zhengyao Jiang; Pasquale Minervini; Minqi Jiang; Tim Rocktäschel (AAMAS, 2021)

Graph Backup: Data Efficient Backup Exploiting Markovian Transitions. - Zhengyao Jiang; Tianjun Zhang; Robert Kirk; Tim Rocktäschel; Edward Grefenstette (CoRR, 2022)

Efficient Planning in a Compact Latent Action Space. - Zhengyao Jiang; Tianjun Zhang; Michael Janner; Yueying Li; Tim Rocktäschel; Edward Grefenstette; Yuandong Tian (ICLR, 2023)

Optimal Transport for Offline Imitation Learning. - Yicheng Luo; Zhengyao Jiang; Samuel Cohen; Edward Grefenstette; Marc Peter Deisenroth (ICLR, 2023)

H-GAP: Humanoid Control with a Generalist Planner. - Zhengyao Jiang; Yingchen Xu; Nolan Wagener; Yicheng Luo; Michael Janner; Edward Grefenstette; Tim Rocktäschel; Yuandong Tian (ICLR, 2024)

Mildly Constrained Evaluation Policy for Offline Reinforcement Learning. - Linjie Xu; Zhengyao Jiang; Jinyu Wang; Lei Song 001; Jiang Bian 002 (Trans. Mach. Learn. Res., 2024)

Multidimensional Directionality-Enhanced Segmentation via large vision model. - Xingru Huang; Changpeng Yue; Yihao Guo; Jian Huang 015; Zhengyao Jiang; Mingkuan Wang; Zhaoyang Xu; Guangyuan Zhang; Jin Liu; Tianyun Zhang; Zhiwen Zheng; Xiaoshuai Zhang; et al. (Medical Image Anal., 2025)

AIDE: AI-Driven Exploration in the Space of Code. - Zhengyao Jiang; Dominik Schmidt; Dhruv Srikanth; Dixing Xu; Ian Kaplan; Deniss Jacenko; Yuxiang Wu (CoRR, 2025)