Jack Lanchantin
Jack Lanchantin
Facebook AI Research
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Zitiert von
Zitiert von
Opportunities and Obstacles for Deep Learning in Biology and Medicine
T Ching, DS Himmelstein, BK Beaulieu-Jones, AA Kalinin, BT Do, ...
Journal of the Royal Society Interface 2018, 2018
Black-Box Generation of Adversarial Text Sequences to Evade Deep Learning Classifiers
J Gao, J Lanchantin, ML Soffa, Y Qi
1st Deep Learning And Security Workshop (DLS18), 2018
DeepChrome: Deep-Learning for Predicting Gene Expression from Histone Modifications
R Singh, J Lanchantin, G Robins, Y Qi
Bioinformatics 2016, 2016
Deep Motif Dashboard: Visualizing and Understanding Genomic Sequences Using Deep Neural Networks
J Lanchantin, R Singh, Z Lin, B Wang, Y Qi
Pacific Symposium on Biocomputing (PSB) 2017, 2016
Deep motif: Visualizing genomic sequence classifications
J Lanchantin, R Singh, Z Lin, Y Qi
ICLR Workshop Track 2016, 2016
General Multi-label Image Classification with Transformers
J Lanchantin, T Wang, V Ordonez, Y Qi
CVPR 2021, 2020
Attend and Predict: Understanding Gene Regulation by Selective Attention on Chromatin
R Singh, J Lanchantin, A Sekhon, Y Qi
31st Conference on Neural Information Processing Systems (NeurIPS 2017), 2017
Reevaluating adversarial examples in natural language
J Morris, E Lifland, J Lanchantin, Y Ji, Y Qi
EMNLP Findings 2020, 2020
MUST-CNN: A Multilayer Shift-and-Stitch Deep Convolutional Architecture for Sequence-Based Protein Structure Prediction
Z Lin, J Lanchantin, Y Qi
30th AAAI Conference on Artificial Intelligence (AAAI 2016), 2016
Neural Message Passing for Multi-Label Classification
J Lanchantin, A Sekhon, Y Qi
European Conference on Machine Learning (ECML-PKDD) 2019, 2019
GaKCo: A Fast Gapped k-mer String Kernel Using Counting
R Singh, A Sekhon, K Kowsari, J Lanchantin, B Wang, Y Qi
Joint European Conference on Machine Learning and Knowledge Discovery in …, 2017
Graph Convolutional Networks for Epigenetic State Prediction Using Both Sequence and 3D Genome Data
J Lanchantin, Y Qi
Bioinformatics 2020, 840173, 2020
FastSK: fast sequence analysis with gapped string kernels
D Blakely, E Collins, R Singh, A Norton, J Lanchantin, Y Qi
Bioinformatics 36, i857-i865, 2020
Transfer Learning for Predicting Virus-Host Protein Interactions for Novel Virus Sequences
J Lanchantin, A Sekhon, C Miller, Y Qi
bioRxiv, 2020
Transfer string kernel for cross-context DNA-protein binding prediction
R Singh, J Lanchantin, G Robins, Y Qi
IEEE/ACM transactions on computational biology and bioinformatics 16 (5 …, 2016
Prototype Matching Networks for Large-Scale Multi-label Genomic Sequence Classification
J Lanchantin, A Sekhon, R Singh, Y Qi
arXiv preprint arXiv:1710.11238, 2017
Memory Matching Networks for Genomic Sequence Classification
J Lanchantin, R Singh, Y Qi
International Conference on Learning Representations (ICLR) workshop track 2017, 2017
Time and Space Complexity of Graph Convolutional Networks
D Blakely, J Lanchantin, Y Qi
Exploring the naturalness of buggy code with recurrent neural networks
J Lanchantin, J Gao
arXiv preprint arXiv:1803.08793, 2016
MCTSBug: Generating Adversarial Text Sequences via Monte Carlo Tree Search and Homoglyph Attack
J Gao, J Lanchantin, Y Qi
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