| Supervised multimodal bitransformers for classifying images and text D Kiela, S Bhooshan, H Firooz, E Perez, D Testuggine arXiv preprint arXiv:1909.02950, 2019 | 216 | 2019 |
| Are natural language inference models IMPPRESsive? Learning IMPlicature and PRESupposition P Jeretic, A Warstadt, S Bhooshan, A Williams arXiv preprint arXiv:2004.03066, 2020 | 96 | 2020 |
| Drive2vec: Multiscale state-space embedding of vehicular sensor data D Hallac, S Bhooshan, M Chen, K Abida, J Leskovec 2018 21st International Conference on Intelligent Transportation Systems …, 2018 | 39 | 2018 |
| Shortfuse: Biomedical time series representations in the presence of structured information M Fiterau, S Bhooshan, J Fries, C Bournhonesque, J Hicks, E Halilaj, ... Machine Learning for Healthcare Conference, 59-74, 2017 | 32 | 2017 |
| Evaluating Generative Models for Text Generation P Kawthekar, R Rewari, S Bhooshan | 20 | 2017 |
| Needles in haystacks: On classifying tiny objects in large images N Pawlowski, S Bhooshan, N Ballas, F Ciompi, B Glocker, M Drozdzal arXiv preprint arXiv:1908.06037, 2019 | 18 | 2019 |
| Predicting Solutions to the Optimal Power Flow Problem T Navidi, S Bhooshan, A Garg | 13 | 2016 |
| Similarity-based lstms for time series representation learning in the presence of structured covariates M Fiterau, J Fries, E Halilaj, N Siranart, S Bhooshan, C Re 29th Conference on Neural Information Processing Systems 3, 2016 | 8 | 2016 |
| Supervised multimodal bitransformers for classifying images and text. arXiv 2019 D Kiela, S Bhooshan, H Firooz, E Perez, D Testuggine arXiv preprint arXiv:1909.02950, 0 | 5 | |
| Automated Nuclei Detection SBA Garg, W Marshall | | 2018 |
| Edge direction prediction of sporting tournaments graphs S Bhooshan, W Lu, J King http://snap.stanford.edu/class/cs224w-2016/projects/cs224w-30-final.pdf, 2016 | | 2016 |
Douwe KielaContextual AI, Stanford UniversityVerified email at stanford.edu
