| Next-generation machine learning for biological networks DM Camacho, KM Collins, RK Powers, JC Costello, JJ Collins Cell 173 (7), 1581-1592, 2018 | 966 | 2018 |
| Harms from increasingly agentic algorithmic systems A Chan, R Salganik, A Markelius, C Pang, N Rajkumar, D Krasheninnikov, ... Proceedings of the 2023 ACM Conference on Fairness, Accountability, and …, 2023 | 126* | 2023 |
| Getting aligned on representational alignment I Sucholutsky, L Muttenthaler, A Weller, A Peng, A Bobu, B Kim, BC Love, ... arXiv preprint arXiv:2310.13018, 2023 | 109* | 2023 |
| Sequence-to-function deep learning frameworks for engineered riboregulators JA Valeri, KM Collins, P Ramesh, MA Alcantar, BA Lepe, TK Lu, ... Nature communications 11 (1), 5058, 2020 | 103 | 2020 |
| Structured, flexible, and robust: benchmarking and improving large language models towards more human-like behavior in out-of-distribution reasoning tasks KM Collins, C Wong, J Feng, M Wei, JB Tenenbaum Proceedings of the Annual Meeting of the Cognitive Science Society 44, 2022 | 78 | 2022 |
| Rich Human Feedback for Text-to-Image Generation Y Liang, J He, G Li, P Li, A Klimovskiy, N Carolan, J Sun, J Pont-Tuset, ... CVPR, 2024 | 76 | 2024 |
| Evaluating language models for mathematics through interactions KM Collins, AQ Jiang, S Frieder, L Wong, M Zilka, U Bhatt, T Lukasiewicz, ... Proceedings of the National Academy of Sciences 121 (24), e2318124121, 2024 | 68 | 2024 |
| Eliciting and learning with soft labels from every annotator KM Collins, U Bhatt, A Weller Proceedings of the AAAI Conference on Human Computation and Crowdsourcing 10 …, 2022 | 59 | 2022 |
| Learning signal-agnostic manifolds of neural fields Y Du, K Collins, J Tenenbaum, V Sitzmann Advances in Neural Information Processing Systems (NeurIPS) 34, 2021 | 49 | 2021 |
| Human Uncertainty in Concept-Based AI Systems KM Collins, M Barker, ME Zarlenga, N Raman, U Bhatt, M Jamnik, ... AIES 2023, 2023 | 44 | 2023 |
| Building machines that learn and think with people KM Collins, I Sucholutsky, U Bhatt, K Chandra, L Wong, M Lee, CE Zhang, ... Nature human behaviour 8 (10), 1851-1863, 2024 | 27 | 2024 |
| BioAutoMATED: an end-to-end automated machine learning tool for explanation and design of biological sequences JA Valeri, LR Soenksen, KM Collins, P Ramesh, G Cai, R Powers, ... Cell systems 14 (6), 525-542. e9, 2023 | 24 | 2023 |
| Learning to Receive Help: Intervention-Aware Concept Embedding Models ME Zarlenga, KM Collins, K Dvijotham, A Weller, Z Shams, M Jamnik Advances in Neural Information Processing Systems (NeurIPS) 36, 2024 | 22* | 2024 |
| The neuro-symbolic inverse planning engine (nipe): Modeling probabilistic social inferences from linguistic inputs L Ying, KM Collins, M Wei, CE Zhang, T Zhi-Xuan, A Weller, ... arXiv preprint arXiv:2306.14325, 2023 | 17 | 2023 |
| Large Language Models Must Be Taught to Know What They Don't Know S Kapoor, N Gruver, M Roberts, K Collins, A Pal, U Bhatt, A Weller, ... arXiv preprint arXiv:2406.08391, 2024 | 16 | 2024 |
| On the informativeness of supervision signals I Sucholutsky, RM Battleday, KM Collins, R Marjieh, J Peterson, P Singh, ... Uncertainty in Artificial Intelligence, 2036-2046, 2023 | 15 | 2023 |
| Learning personalized decision support policies U Bhatt, V Chen, KM Collins, P Kamalaruban, E Kallina, A Weller, ... AAAI, 2025 | 14 | 2025 |
| Deep representation learning improves prediction of LacI-mediated transcriptional repression AS Garruss, KM Collins, GM Church Proceedings of the National Academy of Sciences 118 (27), e2022838118, 2021 | 13 | 2021 |
| Human-in-the-Loop Mixup KM Collins, U Bhatt, W Liu, V Piratla, I Sucholutsky, B Love, A Weller The 39th Conference on Uncertainty in Artificial Intelligence, 2023 | 10 | 2023 |
| Can Large Language Models Understand Symbolic Graphics Programs? Z Qiu, W Liu, H Feng, Z Liu, TZ Xiao, KM Collins, JB Tenenbaum, A Weller, ... arXiv preprint arXiv:2408.08313, 2024 | 9 | 2024 |
Adrian WellerDirector of Research, Machine Learning, University of CambridgeVerified email at eng.cam.ac.uk
