Estimating information flow in deep neural networks Z Goldfeld, E Berg, K Greenewald, I Melnyk, N Nguyen, B Kingsbury, ... arXiv preprint arXiv:1810.05728, 2018 | 178 | 2018 |
Fighting offensive language on social media with unsupervised text style transfer CN Santos, I Melnyk, I Padhi arXiv preprint arXiv:1805.07685, 2018 | 162 | 2018 |
Deep learning algorithm for data-driven simulation of noisy dynamical system K Yeo, I Melnyk Journal of Computational Physics 376, 1212-1231, 2019 | 107 | 2019 |
Tabular transformers for modeling multivariate time series I Padhi, Y Schiff, I Melnyk, M Rigotti, Y Mroueh, P Dognin, J Ross, R Nair, ... ICASSP 2021-2021 IEEE International Conference on Acoustics, Speech and …, 2021 | 77 | 2021 |
Estimating structured vector autoregressive models I Melnyk, A Banerjee International Conference on Machine Learning, 830-839, 2016 | 70 | 2016 |
Optimizing mode connectivity via neuron alignment N Tatro, PY Chen, P Das, I Melnyk, P Sattigeri, R Lai Advances in Neural Information Processing Systems 33, 15300-15311, 2020 | 54 | 2020 |
Semi-Markov switching vector autoregressive model-based anomaly detection in aviation systems I Melnyk, A Banerjee, B Matthews, N Oza Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge …, 2016 | 54 | 2016 |
R2n2: Residual recurrent neural networks for multivariate time series forecasting H Goel, I Melnyk, A Banerjee arXiv preprint arXiv:1709.03159, 2017 | 53 | 2017 |
Vector autoregressive model-based anomaly detection in aviation systems I Melnyk, B Matthews, H Valizadegan, A Banerjee, N Oza Journal of Aerospace Information Systems 13 (4), 161-173, 2016 | 51 | 2016 |
Adversarial semantic alignment for improved image captions P Dognin, I Melnyk, Y Mroueh, J Ross, T Sercu Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2019 | 42 | 2019 |
Image captioning as an assistive technology: lessons learned from VizWiz 2020 challenge P Dognin, I Melnyk, Y Mroueh, I Padhi, M Rigotti, J Ross, Y Schiff, ... Journal of Artificial Intelligence Research 73, 437-459, 2022 | 41 | 2022 |
Cooperative vision-aided inertial navigation using overlapping views IV Melnyk, JA Hesch, SI Roumeliotis 2012 IEEE International Conference on Robotics and Automation, 936-943, 2012 | 37 | 2012 |
Wasserstein barycenter model ensembling P Dognin, I Melnyk, Y Mroueh, J Ross, CD Santos, T Sercu arXiv preprint arXiv:1902.04999, 2019 | 30 | 2019 |
Fold2seq: A joint sequence (1d)-fold (3d) embedding-based generative model for protein design Y Cao, P Das, V Chenthamarakshan, PY Chen, I Melnyk, Y Shen International Conference on Machine Learning, 1261-1271, 2021 | 26 | 2021 |
Improved neural text attribute transfer with non-parallel data I Melnyk, CN Santos, K Wadhawan, I Padhi, A Kumar arXiv preprint arXiv:1711.09395, 2017 | 26 | 2017 |
Detection of precursors to aviation safety incidents due to human factors I Melnyk, P Yadav, M Steinbach, J Srivastava, V Kumar, A Banerjee 2013 IEEE 13th International Conference on Data Mining Workshops, 407-412, 2013 | 21 | 2013 |
Benchmarking deep generative models for diverse antibody sequence design I Melnyk, P Das, V Chenthamarakshan, A Lozano arXiv preprint arXiv:2111.06801, 2021 | 17 | 2021 |
Multivariate aviation time series modeling: VARs vs. LSTMs H Goel, I Melnyk, N Oza, B Matthews, A Banerjee Unpublished manuscript Retrieved from https://www% 20semanticscholar% 20org …, 2016 | 17 | 2016 |
Regen: Reinforcement learning for text and knowledge base generation using pretrained language models PL Dognin, I Padhi, I Melnyk, P Das arXiv preprint arXiv:2108.12472, 2021 | 16 | 2021 |
Reprogramming Pretrained Language Models for Antibody Sequence Infilling I Melnyk, V Chenthamarakshan, PY Chen, P Das, A Dhurandhar, I Padhi, ... | 14 | 2023 |