| Text mining with n-gram variables M Schonlau, N Guenther, I Sucholutsky The Stata Journal 17 (4), 866-881, 2017 | 55* | 2017 |
| Soft-Label Dataset Distillation and Text Dataset Distillation I Sucholutsky, M Schonlau arXiv preprint arXiv:1910.02551, 2019 | 51 | 2019 |
| 'Less Than One'-Shot Learning: Learning N Classes From M< N Samples I Sucholutsky, M Schonlau Proceedings of the AAAI Conference on Artificial Intelligence 35 (11), 9739-9746, 2021 | 43 | 2021 |
| Deep Learning for System Trace Restoration I Sucholutsky, A Narayan, M Schonlau, S Fischmeister 2019 International Joint Conference on Neural Networks (IJCNN), 2019 | 8 | 2019 |
| SecDD: Efficient and Secure Method for Remotely Training Neural Networks (Student Abstract) I Sucholutsky, M Schonlau Proceedings of the AAAI Conference on Artificial Intelligence 35 (18), 15897 …, 2021 | 7* | 2021 |
| Words are all you need? Capturing human sensory similarity with textual descriptors R Marjieh, P van Rijn, I Sucholutsky, TR Sumers, H Lee, TL Griffiths, ... arXiv preprint arXiv:2206.04105, 2022 | 4 | 2022 |
| Pay attention and you won’t lose it: a deep learning approach to sequence imputation I Sucholutsky, A Narayan, M Schonlau, S Fischmeister PeerJ Computer Science 5 (e210), 2019 | 3 | 2019 |
| Can Humans Do Less-Than-One-Shot Learning? M Malaviya, I Sucholutsky, K Oktar, TL Griffiths arXiv preprint arXiv:2202.04670, 2022 | 2 | 2022 |
| Predicting human similarity judgments using large language models R Marjieh, I Sucholutsky, TR Sumers, N Jacoby, TL Griffiths arXiv preprint arXiv:2202.04728, 2022 | 2 | 2022 |
| One Line To Rule Them All: Generating LO-Shot Soft-Label Prototypes I Sucholutskv, NH Kim, RP Browne, M Schonlau 2021 International Joint Conference on Neural Networks (IJCNN), 1-8, 2021 | 2 | 2021 |
| Optimal 1-NN prototypes for pathological geometries I Sucholutsky, M Schonlau PeerJ Computer Science 7, e464, 2021 | 2 | 2021 |
| On the Informativeness of Supervision Signals I Sucholutsky, R Marjieh, N Jacoby, TL Griffiths arXiv preprint arXiv:2211.01407, 2022 | 1 | 2022 |
| Analyzing Diffusion as Serial Reproduction R Marjieh, I Sucholutsky, TA Langlois, N Jacoby, TL Griffiths arXiv preprint arXiv:2209.14821, 2022 | 1 | 2022 |
| Human Uncertainty in Concept-Based AI Systems KM Collins, M Barker, ME Zarlenga, N Raman, U Bhatt, M Jamnik, ... arXiv preprint arXiv:2303.12872, 2023 | | 2023 |
| Around the world in 60 words: A generative vocabulary test for online research P van Rijn, Y Sun, H Lee, R Marjieh, I Sucholutsky, F Lanzarini, E André, ... arXiv preprint arXiv:2302.01614, 2023 | | 2023 |
| What Language Reveals about Perception: Distilling Psychophysical Knowledge from Large Language Models R Marjieh, I Sucholutsky, P van Rijn, N Jacoby, TL Griffiths arXiv preprint arXiv:2302.01308, 2023 | | 2023 |
| Alignment with human representations supports robust few-shot learning I Sucholutsky, TL Griffiths arXiv preprint arXiv:2301.11990, 2023 | | 2023 |
| Playing the Lottery of a Lifetime: The Effect of Socially Induced Aspiration on Q-Learning Agents Y Hatekar, R Dubey, T Sumers, I Sucholutsky Proceedings of the Annual Meeting of the Cognitive Science Society 44 (44), 2022 | | 2022 |
| Learning From Almost No Data I Sucholutsky University of Waterloo, 2021 | | 2021 |
| ConvART: Improving Adaptive Resonance Theory for Unsupervised Image Clustering I Sucholutsky, M Schonlau Journal of Computational Vision and Imaging Systems 4 (1), 3, 2018 | | 2018 |
Matthias SchonlauUniversity of WaterlooVerified email at uwaterloo.ca
