Jack Lanchantin

According to our database¹, Jack Lanchantin authored at least 20 papers between 2016 and 2024.

Collaborative distances:

Dijkstra number² of four.
Erdős number³ of four.

Timeline

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PhD thesis

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On csauthors.net:

Bibliography

2024

TOOLVERIFIER: Generalization to New Tools via Self-Verification.

[BibT_eX]

[DOI]

CoRR, 2024

2023

Learning to Reason and Memorize with Self-Notes.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Robustness of Named-Entity Replacements for In-Context Learning.

[BibT_eX]

[DOI]

Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2023, 2023

A Data Source for Reasoning Embodied Agents.

[BibT_eX]

[DOI]

Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2021

General Multi-Label Image Classification With Transformers.

[BibT_eX]

[DOI]

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2021

Transfer learning for predicting virus-host protein interactions for novel virus sequences.

[BibT_eX]

[DOI]

Proceedings of the BCB '21: 12th ACM International Conference on Bioinformatics, 2021

2020

Reevaluating Adversarial Examples in Natural Language.

[BibT_eX]

[DOI]

Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2020, 2020

2019

Transfer String Kernel for Cross-Context DNA-Protein Binding Prediction.

[BibT_eX]

[DOI]

IEEE ACM Trans. Comput. Biol. Bioinform., 2019

Neural Message Passing for Multi-label Classification.

[BibT_eX]

[DOI]

Jack Lanchantin

Arshdeep Sekhon

Yanjun Qi

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2019

2018

Exploring the Naturalness of Buggy Code with Recurrent Neural Networks.

[BibT_eX]

[DOI]

Jack Lanchantin

Ji Gao

CoRR, 2018

Black-Box Generation of Adversarial Text Sequences to Evade Deep Learning Classifiers.

[BibT_eX]

[DOI]

Proceedings of the 2018 IEEE Security and Privacy Workshops, 2018

2017

Prototype Matching Networks for Large-Scale Multi-label Genomic Sequence Classification.

[BibT_eX]

[DOI]

CoRR, 2017

Deep Motif Dashboard: Visualizing and Understanding Genomic Sequences Using Deep Neural Networks.

[BibT_eX]

[DOI]

Proceedings of the Biocomputing 2017: Proceedings of the Pacific Symposium, 2017

GaKCo: A Fast Gapped k-mer String Kernel Using Counting.

[BibT_eX]

[DOI]

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2017

Attend and Predict: Understanding Gene Regulation by Selective Attention on Chromatin.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Memory Matching Networks for Genomic Sequence Classification.

[BibT_eX]

[DOI]

Jack Lanchantin

Ritambhara Singh

Yanjun Qi

Proceedings of the 5th International Conference on Learning Representations, 2017

2016

Deep GDashboard: Visualizing and Understanding Genomic Sequences Using Deep Neural Networks.

[BibT_eX]

[DOI]

CoRR, 2016

Deep Motif: Visualizing Genomic Sequence Classifications.

[BibT_eX]

[DOI]

CoRR, 2016

DeepChrome: deep-learning for predicting gene expression from histone modifications.

[BibT_eX]

[DOI]

Bioinform., 2016

MUST-CNN: A Multilayer Shift-and-Stitch Deep Convolutional Architecture for Sequence-Based Protein Structure Prediction.

[BibT_eX]

[DOI]

Zeming Lin

Jack Lanchantin

Yanjun Qi

Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence, 2016

Jack Lanchantin

Timeline

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On csauthors.net:

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