| Gotta go fast when generating data with score-based models A Jolicoeur-Martineau, K Li, R Piché-Taillefer, T Kachman, I Mitliagkas arXiv preprint arXiv:2105.14080, 2021 | 180 | 2021 |
| Gradients are not all you need L Metz, CD Freeman, SS Schoenholz, T Kachman arXiv preprint arXiv:2111.05803, 2021 | 78 | 2021 |
| Self-organized resonance during search of a diverse chemical space T Kachman, JA Owen, JL England Physical review letters 119 (3), 038001, 2017 | 62 | 2017 |
| Computer vision-based recognition of liquid surfaces and phase boundaries in transparent vessels, with emphasis on chemistry applications S Eppel, T Kachman arXiv preprint arXiv:1404.7174, 2014 | 41 | 2014 |
| Safe reinforcement learning from pixels using a stochastic latent representation Y Hogewind, TD Simao, T Kachman, N Jansen The Eleventh International Conference on Learning Representations, 2022 | 10 | 2022 |
| Anomalous diffusion: fractional Brownian motion vs fractional Ito motion I Eliazar, T Kachman Journal of Physics A: Mathematical and Theoretical 55 (11), 115002, 2022 | 10 | 2022 |
| Lyapunov exponents for diversity in differentiable games J Lorraine, P Vicol, J Parker-Holder, T Kachman, L Metz, J Foerster arXiv preprint arXiv:2112.14570, 2021 | 9 | 2021 |
| Generating and imputing tabular data via diffusion and flow-based gradient-boosted trees A Jolicoeur-Martineau, K Fatras, T Kachman International Conference on Artificial Intelligence and Statistics, 1288-1296, 2024 | 8 | 2024 |
| Neural payoff machines: Predicting fair and stable payoff allocations among team members D Cornelisse, T Rood, Y Bachrach, M Malinowski, T Kachman Advances in Neural Information Processing Systems 35, 25491-25503, 2022 | 8 | 2022 |
| Learning multiple non-mutually-exclusive tasks for improved classification of inherently ordered labels V Ratner, Y Shoshan, T Kachman arXiv preprint arXiv:1805.11837, 2018 | 7 | 2018 |
| Numerical implementation of the multiscale and averaging methods for quasi periodic systems T Kachman, S Fishman, A Soffer Computer Physics Communications 221 (December 2017), 235-245, 2017 | 7 | 2017 |
| Using bifurcations for diversity in differentiable games J Lorraine, J Parker-Holder, P Vicol, A Pacchiano, L Metz, T Kachman, ... ICML 2021 Beyond First Order Methods Workshop, 2021 | 5 | 2021 |
| Bias correction in deep learning systems LH John A. Gunnels, Tal Kachman, Catherine H. Crawford US Patent P201,806,931, 2019 | 5* | 2019 |
| Novel Uncertainty Framework for Deep Learning Ensembles T Kachman, M Moshkovitz, M Rosen-Zvi NeurIPS Bayesian Deep Learning workshop, 2018 | 4 | 2018 |
| Explainability Techniques for Chemical Language Models S Hödl, W Robinson, Y Bachrach, W Huck, T Kachman arXiv preprint arXiv:2305.16192, 2023 | 3 | 2023 |
| Quantum topological classification T Kachman, KL Clarkson, MS Squillante, L Horesh, IY Akhalwaya US Patent 11,741,391, 2023 | 2 | 2023 |
| Diffusion models with location-scale noise A Jolicoeur-Martineau, K Fatras, K Li, T Kachman arXiv preprint arXiv:2304.05907, 2023 | 2 | 2023 |
| Gotta go fast with score-based generative models A Jolicoeur-Martineau, K Li, R Piché-Taillefer, T Kachman, I Mitliagkas The Symbiosis of Deep Learning and Differential Equations, 2021 | 2 | 2021 |
| Sketching using a hybrid quantum-classical system JAG Catherine H. Crawford, Lior Horesh, Tal Kachman US Patent P201,806,929, 2019 | 2* | 2019 |
| Using cooperative game theory to prune neural networks M Diaz-Ortiz Jr, B Kempinski, D Cornelisse, Y Bachrach, T Kachman arXiv preprint arXiv:2311.10468, 2023 | 1 | 2023 |
Alexia Jolicoeur-MartineauSamsung - SAIT AI Lab Montreal在 mail.mcgill.ca 的电子邮件经过验证
