| 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 | 233 | 2018 |
| Fighting offensive language on social media with unsupervised text style transfer CN Santos, I Melnyk, I Padhi arXiv preprint arXiv:1805.07685, 2018 | 200 | 2018 |
| 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 | 156 | 2021 |
| Deep learning algorithm for data-driven simulation of noisy dynamical system K Yeo, I Melnyk Journal of Computational Physics 376, 1212-1231, 2019 | 134 | 2019 |
| 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 | 95 | 2020 |
| Estimating structured vector autoregressive models I Melnyk, A Banerjee International Conference on Machine Learning, 830-839, 2016 | 84 | 2016 |
| 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 | 73 | 2022 |
| R2n2: Residual recurrent neural networks for multivariate time series forecasting H Goel, I Melnyk, A Banerjee arXiv preprint arXiv:1709.03159, 2017 | 73 | 2017 |
| 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 | 69 | 2016 |
| 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 | 67 | 2016 |
| Knowledge Graph Generation From Text I Melnyk, P Dognin, P Das arXiv preprint arXiv:2211.10511, 2022 | 59 | 2022 |
| Reprogramming pretrained language models for antibody sequence infilling I Melnyk, V Chenthamarakshan, PY Chen, P Das, A Dhurandhar, I Padhi, ... International Conference on Machine Learning, 24398-24419, 2023 | 52 | 2023 |
| 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 | 45 | 2019 |
| 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 | 43 | 2012 |
| Wasserstein barycenter model ensembling P Dognin, I Melnyk, Y Mroueh, J Ross, CD Santos, T Sercu arXiv preprint arXiv:1902.04999, 2019 | 40 | 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 | 37 | 2021 |
| Larimar: Large Language Models with Episodic Memory Control P Das, S Chaudhury, E Nelson, I Melnyk, S Swaminathan, S Dai, ... arXiv preprint arXiv:2403.11901, 2024 | 35 | 2024 |
| Grapher: Multi-stage knowledge graph construction using pretrained language models I Melnyk, P Dognin, P Das NeurIPS 2021 Workshop on Deep Generative Models and Downstream Applications, 2021 | 34 | 2021 |
| Distributional preference alignment of llms via optimal transport I Melnyk, Y Mroueh, B Belgodere, M Rigotti, A Nitsure, M Yurochkin, ... Advances in Neural Information Processing Systems 37, 104412-104442, 2024 | 32 | 2024 |
| 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 | 32 | 2021 |
Payel DasManager and Principal Research Staff Member, AI research, IBM Watson, NYVerified email at us.ibm.com
