MUST-CNN: A Multilayer Shift-and-Stitch Deep Convolutional Architecture for Sequence-Based Protein Structure Prediction. - Zeming Lin; Jack Lanchantin; Yanjun Qi (AAAI, 2016)

Deep Motif: Visualizing Genomic Sequence Classifications. - Jack Lanchantin; Ritambhara Singh; Zeming Lin; Yanjun Qi (CoRR, 2016)

TorchCraft: a Library for Machine Learning Research on Real-Time Strategy Games. - Gabriel Synnaeve; Nantas Nardelli; Alex Auvolat; Soumith Chintala; Timothée Lacroix; Zeming Lin; Florian Richoux; Nicolas Usunier (CoRR, 2016)

Episodic Exploration for Deep Deterministic Policies: An Application to StarCraft Micromanagement Tasks. - Nicolas Usunier; Gabriel Synnaeve; Zeming Lin; Soumith Chintala (CoRR, 2016)

An Analysis of Model-Based Heuristic Search Techniques for StarCraft Combat Scenarios. - David Churchill; Zeming Lin; Gabriel Synnaeve (AIIDE Workshops, 2017)

STARDATA: A StarCraft AI Research Dataset. - Zeming Lin; Jonas Gehring; Vasil Khalidov; Gabriel Synnaeve (AIIDE, 2017)

DeepCloak: Masking Deep Neural Network Models for Robustness Against Adversarial Samples. - Ji Gao; Beilun Wang; Zeming Lin; Weilin Xu; Yanjun Qi (ICLR (Workshop), 2017)

Episodic Exploration for Deep Deterministic Policies for StarCraft Micromanagement. - Nicolas Usunier; Gabriel Synnaeve; Zeming Lin; Soumith Chintala (ICLR (Poster), 2017)

Intrinsic Motivation and Automatic Curricula via Asymmetric Self-Play. - Sainbayar Sukhbaatar; Zeming Lin; Ilya Kostrikov; Gabriel Synnaeve; Arthur Szlam; Rob Fergus (ICLR (Poster), 2018)

Forward Modeling for Partial Observation Strategy Games - A StarCraft Defogger. - Gabriel Synnaeve; Zeming Lin; Jonas Gehring; Daniel Gant; Vegard Mella; Vasil Khalidov; Nicolas Carion; Nicolas Usunier (NeurIPS, 2018)

Value Propagation Networks. - Nantas Nardelli; Gabriel Synnaeve; Zeming Lin; Pushmeet Kohli; Philip H. S. Torr; Nicolas Usunier (ICLR (Poster), 2019)

PyTorch: An Imperative Style, High-Performance Deep Learning Library. - Adam Paszke; Sam Gross; Francisco Massa; Adam Lerer; James Bradbury; Gregory Chanan; Trevor Killeen; Zeming Lin; Natalia Gimelshein; Luca Antiga; Alban Desmaison; Andreas Köpf; et al. (NeurIPS, 2019)

基于非线性模糊矩阵的代码混淆有效性评估模型 (Code Obfuscation Effectiveness Assessment Model Based on Nonlinear Fuzzy Matrices). - Qing Su; Zeming Lin; Zhiyi Lin; Jianfeng Huang (计算机科学, 2019)

Growing Action Spaces. - Gregory Farquhar; Laura Gustafson; Zeming Lin; Shimon Whiteson; Nicolas Usunier; Gabriel Synnaeve (ICML, 2020)

Biological structure and function emerge from scaling unsupervised learning to 250 million protein sequences. - Alexander Rives; Joshua Meier; Tom Sercu; Siddharth Goyal; Zeming Lin; Jason Liu; Demi Guo; Myle Ott; C. Lawrence Zitnick; Jerry Ma; Rob Fergus (Proc. Natl. Acad. Sci. USA, 2021)

Learning inverse folding from millions of predicted structures. - Chloe Hsu; Robert Verkuil; Jason Liu; Zeming Lin; Brian Hie; Tom Sercu; Adam Lerer; Alexander Rives (ICML, 2022)

Predictive and Generative Models of Protein Sequence and Structure - Zeming Lin (2024)