Katherine M. Collins

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Adrian WellerDirector of Research, Machine Learning, University of CambridgeDirección de correo verificada de eng.cam.ac.uk
Diogo M. CamachoVice President, Computational Biology @ CellarityDirección de correo verificada de cellarity.com
Umang BhattNew York UniversityDirección de correo verificada de nyu.edu
Joshua B. TenenbaumMITDirección de correo verificada de mit.edu
Krishnamurthy DvijothamGoogle DeepMindDirección de correo verificada de cs.washington.edu
Timothy LuMassachusetts Institute of TechnologyDirección de correo verificada de mit.edu
Ilia SucholutskyPrinceton UniversityDirección de correo verificada de princeton.edu
Mateo Espinosa ZarlengaUniversity of CambridgeDirección de correo verificada de cam.ac.uk
Vincent SitzmannAssistant Professor, Massachusetts Institute of TechnologyDirección de correo verificada de mit.edu
Yilun DuMITDirección de correo verificada de mit.edu
Bradley C. LoveProfessor of Cognitive and Decision Sciences, University College LondonDirección de correo verificada de ucl.ac.uk
George ChurchHarvard Medical SchoolDirección de correo verificada de harvard.edu
Alexander S. Garruss (Garrett)Harvard UniversityDirección de correo verificada de fas.harvard.edu
Thomas L. GriffithsProfessor of Psychology and Computer Science, Princeton UniversityDirección de correo verificada de princeton.edu
Samuel GershmanProfessor, Harvard UniversityDirección de correo verificada de fas.harvard.edu
Tuan Anh LeResearch Scientist, Google ResearchDirección de correo verificada de google.com
Kevin EllisCornellDirección de correo verificada de cornell.edu
Luke HewittStanford UniversityDirección de correo verificada de stanford.edu
Lionel Catherine WongMassachusetts Institute of Technology

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Katherine M. Collins

Machine Learning PhD Student at the University of Cambridge

Dirección de correo verificada de cam.ac.uk - Página principal

Machine Learning Bayesian Inference Trustworthy ML Human-Machine Teams


Título Ordenar por citas Ordenar por año Ordenar por título	Citado por Citado por	Año
Next-generation machine learning for biological networks DM Camacho, KM Collins, RK Powers, JC Costello, JJ Collins Cell 173 (7), 1581-1592, 2018	856	2018
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	85	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	48	2022
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	43*	2023
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	38	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	37	2021
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	20	2023
Human Uncertainty in Concept-Based AI Systems KM Collins, M Barker, ME Zarlenga, N Raman, U Bhatt, M Jamnik, ... AIES 2023, 2023	19	2023
Evaluating language models for mathematics through interactions KM Collins, AQ Jiang, S Frieder, L Wong, M Zilka, U Bhatt, T Lukasiewicz, ... arXiv preprint arXiv:2306.01694, 2023	15	2023
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	10	2021
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	8	2023
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	8	2023
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	8*	2023
Learning personalized decision support policies U Bhatt, V Chen, KM Collins, P Kamalaruban, E Kallina, A Weller, ... arXiv preprint arXiv:2304.06701, 2023	7	2023
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	5	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	4	2024
Hybrid Memoised Wake-Sleep: Approximate Inference at the Discrete-Continuous Interface TA Le, KM Collins, L Hewitt, K Ellis, SJ Gershman, JB Tenenbaum International Conference on Learning Representations (ICLR), 2022	4	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, ... arXiv preprint arXiv:2312.10240, 2023	3	2023
Selective Concept Models: Permitting Stakeholder Customisation at Test-Time M Barker, KM Collins, K Dvijotham, A Weller, U Bhatt Proceedings of the AAAI Conference on Human Computation and Crowdsourcing, 2023	3	2023
Feedbacklogs: Recording and incorporating stakeholder feedback into machine learning pipelines M Barker, E Kallina, D Ashok, K Collins, A Casovan, A Weller, A Talwalkar, ... Proceedings of the 3rd ACM Conference on Equity and Access in Algorithms …, 2023	2	2023

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