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Journal Articles
- 2019
[j2]Ritambhara Singh
, Jack Lanchantin, Gabriel Robins, Yanjun Qi:
Transfer String Kernel for Cross-Context DNA-Protein Binding Prediction. IEEE ACM Trans. Comput. Biol. Bioinform. 16(5): 1524-1536 (2019)- 2016
- [j1]Ritambhara Singh, Jack Lanchantin, Gabriel Robins, Yanjun Qi:
DeepChrome: deep-learning for predicting gene expression from histone modifications. Bioinform. 32(17): 639-648 (2016)
Conference and Workshop Papers
- 2023
- [c13]Jack Lanchantin, Sainbayar Sukhbaatar, Gabriel Synnaeve, Yuxuan Sun, Kavya Srinet, Arthur Szlam:
A Data Source for Reasoning Embodied Agents. AAAI 2023: 8438-8446 - [c12]Saeed Goodarzi, Nikhil Kagita, Dennis Minn, Shufan Wang, Roberto Dessì, Shubham Toshniwal, Adina Williams, Jack Lanchantin, Koustuv Sinha:
Robustness of Named-Entity Replacements for In-Context Learning. EMNLP (Findings) 2023: 10914-10931 - [c11]Jack Lanchantin, Shubham Toshniwal, Jason Weston, Arthur Szlam, Sainbayar Sukhbaatar:
Learning to Reason and Memorize with Self-Notes. NeurIPS 2023 - 2021
- [c10]Jack Lanchantin, Tom Weingarten, Arshdeep Sekhon, Clint Miller, Yanjun Qi:
Transfer learning for predicting virus-host protein interactions for novel virus sequences. BCB 2021: 36:1-36:10 - [c9]Jack Lanchantin, Tianlu Wang, Vicente Ordonez, Yanjun Qi:
General Multi-Label Image Classification With Transformers. CVPR 2021: 16478-16488 - 2020
- [c8]John X. Morris, Eli Lifland, Jack Lanchantin, Yangfeng Ji, Yanjun Qi:
Reevaluating Adversarial Examples in Natural Language. EMNLP (Findings) 2020: 3829-3839 - 2019
- [c7]Jack Lanchantin, Arshdeep Sekhon, Yanjun Qi:
Neural Message Passing for Multi-label Classification. ECML/PKDD (2) 2019: 138-163 - 2018
- [c6]Ji Gao, Jack Lanchantin, Mary Lou Soffa, Yanjun Qi:
Black-Box Generation of Adversarial Text Sequences to Evade Deep Learning Classifiers. IEEE Symposium on Security and Privacy Workshops 2018: 50-56 - 2017
- [c5]Jack Lanchantin, Ritambhara Singh, Yanjun Qi:
Memory Matching Networks for Genomic Sequence Classification. ICLR (Workshop) 2017 - [c4]Ritambhara Singh, Jack Lanchantin, Arshdeep Sekhon, Yanjun Qi:
Attend and Predict: Understanding Gene Regulation by Selective Attention on Chromatin. NIPS 2017: 6785-6795 - [c3]Ritambhara Singh, Arshdeep Sekhon, Kamran Kowsari, Jack Lanchantin, Beilun Wang, Yanjun Qi:
GaKCo: A Fast Gapped k-mer String Kernel Using Counting. ECML/PKDD (1) 2017: 356-373 - [c2]Jack Lanchantin, Ritambhara Singh, Beilun Wang, Yanjun Qi:
Deep Motif Dashboard: Visualizing and Understanding Genomic Sequences Using Deep Neural Networks. PSB 2017: 254-265 - 2016
- [c1]Zeming Lin, Jack Lanchantin, Yanjun Qi:
MUST-CNN: A Multilayer Shift-and-Stitch Deep Convolutional Architecture for Sequence-Based Protein Structure Prediction. AAAI 2016: 27-34
Informal and Other Publications
- 2024
- [i17]Dheeraj Mekala, Jason Weston, Jack Lanchantin, Roberta Raileanu, Maria Lomeli, Jingbo Shang, Jane Dwivedi-Yu:
TOOLVERIFIER: Generalization to New Tools via Self-Verification. CoRR abs/2402.14158 (2024) - 2023
- [i16]Jack Lanchantin, Shubham Toshniwal, Jason Weston, Arthur Szlam, Sainbayar Sukhbaatar:
Learning to Reason and Memorize with Self-Notes. CoRR abs/2305.00833 (2023) - [i15]Jack Lanchantin, Sainbayar Sukhbaatar, Gabriel Synnaeve, Yuxuan Sun, Kavya Srinet, Arthur Szlam:
A Data Source for Reasoning Embodied Agents. CoRR abs/2309.07974 (2023) - 2020
- [i14]John X. Morris, Eli Lifland, Jack Lanchantin, Yangfeng Ji, Yanjun Qi:
Reevaluating Adversarial Examples in Natural Language. CoRR abs/2004.14174 (2020) - [i13]Jack Lanchantin, Tianlu Wang, Vicente Ordonez, Yanjun Qi:
General Multi-label Image Classification with Transformers. CoRR abs/2011.14027 (2020) - 2019
- [i12]Jack Lanchantin, Arshdeep Sekhon, Yanjun Qi:
Neural Message Passing for Multi-Label Classification. CoRR abs/1904.08049 (2019) - 2018
- [i11]Ji Gao, Jack Lanchantin, Mary Lou Soffa, Yanjun Qi:
Black-box Generation of Adversarial Text Sequences to Evade Deep Learning Classifiers. CoRR abs/1801.04354 (2018) - [i10]Jack Lanchantin, Ji Gao:
Exploring the Naturalness of Buggy Code with Recurrent Neural Networks. CoRR abs/1803.08793 (2018) - 2017
- [i9]Jack Lanchantin, Ritambhara Singh, Yanjun Qi:
Memory Matching Networks for Genomic Sequence Classification. CoRR abs/1702.06760 (2017) - [i8]Ritambhara Singh, Arshdeep Sekhon, Kamran Kowsari, Jack Lanchantin, Beilun Wang, Yanjun Qi:
GaKCo: a Fast GApped k-mer string Kernel using COunting. CoRR abs/1704.07468 (2017) - [i7]Ritambhara Singh, Jack Lanchantin, Arshdeep Sekhon, Yanjun Qi:
Attend and Predict: Understanding Gene Regulation by Selective Attention on Chromatin. CoRR abs/1708.00339 (2017) - [i6]Jack Lanchantin, Arshdeep Sekhon, Ritambhara Singh, Yanjun Qi:
Prototype Matching Networks for Large-Scale Multi-label Genomic Sequence Classification. CoRR abs/1710.11238 (2017) - 2016
- [i5]Jack Lanchantin, Ritambhara Singh, Zeming Lin, Yanjun Qi:
Deep Motif: Visualizing Genomic Sequence Classifications. CoRR abs/1605.01133 (2016) - [i4]Zeming Lin, Jack Lanchantin, Yanjun Qi:
MUST-CNN: A Multilayer Shift-and-Stitch Deep Convolutional Architecture for Sequence-based Protein Structure Prediction. CoRR abs/1605.03004 (2016) - [i3]Ritambhara Singh, Jack Lanchantin, Gabriel Robins, Yanjun Qi:
DeepChrome: Deep-learning for predicting gene expression from histone modifications. CoRR abs/1607.02078 (2016) - [i2]Jack Lanchantin, Ritambhara Singh, Beilun Wang, Yanjun Qi:
Deep GDashboard: Visualizing and Understanding Genomic Sequences Using Deep Neural Networks. CoRR abs/1608.03644 (2016) - [i1]Ritambhara Singh, Jack Lanchantin, Gabriel Robins, Yanjun Qi:
Transfer String Kernel for Cross-Context DNA-Protein Binding Prediction. CoRR abs/1609.03490 (2016)
Coauthor Index
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