Nabeel Seedat

Publication Activity (10 Years)

Years Active: 2018-2024
Publications (10 Years): 40

Top Topics

Quantile Regression

Machine Learning Systems

Prediction Intervals

Top Venues

Publications

Nabeel Seedat, Fergus Imrie, Mihaela van der Schaar
Dissecting Sample Hardness: A Fine-Grained Analysis of Hardness Characterization Methods for Data-Centric AI. ICLR (2024)
Lea Goetz, Nabeel Seedat, Robert Vandersluis, Mihaela van der Schaar
Generalization - a key challenge for responsible AI in patient-facing clinical applications. npj Digit. Medicine 7 (1) (2024)
Nabeel Seedat, Fergus Imrie, Mihaela van der Schaar
Dissecting Sample Hardness: A Fine-Grained Analysis of Hardness Characterization Methods for Data-Centric AI. CoRR (2024)
Thomas Pouplin, Alan Jeffares, Nabeel Seedat, Mihaela van der Schaar
Relaxed Quantile Regression: Prediction Intervals for Asymmetric Noise. CoRR (2024)
Tennison Liu, Nicolás Astorga, Nabeel Seedat, Mihaela van der Schaar
Large Language Models to Enhance Bayesian Optimization. CoRR (2024)
Nabeel Seedat, Nicolas Huynh, Fergus Imrie, Mihaela van der Schaar
You can't handle the (dirty) truth: Data-centric insights improve pseudo-labeling. CoRR (2024)
Tennison Liu, Nicolás Astorga, Nabeel Seedat, Mihaela van der Schaar
Large Language Models to Enhance Bayesian Optimization. ICLR (2024)
Nicolas Huynh, Jeroen Berrevoets, Nabeel Seedat, Jonathan Crabbé, Zhaozhi Qian, Mihaela van der Schaar
DAGnosis: Localized Identification of Data Inconsistencies using Structures. AISTATS (2024)
Elisabeth R. M. Heremans, Nabeel Seedat, Bertien Buyse, Dries Testelmans, Mihaela van der Schaar, Maarten De Vos
U-PASS: An uncertainty-guided deep learning pipeline for automated sleep staging. Comput. Biol. Medicine 171 (2024)
Nabeel Seedat, Fergus Imrie, Mihaela van der Schaar
Navigating Data-Centric Artificial Intelligence With DC-Check: Advances, Challenges, and Opportunities. IEEE Trans. Artif. Intell. 5 (6) (2024)
Nicolas Huynh, Jeroen Berrevoets, Nabeel Seedat, Jonathan Crabbé, Zhaozhi Qian, Mihaela van der Schaar
DAGnosis: Localized Identification of Data Inconsistencies using Structures. CoRR (2024)
Lasse Hansen, Nabeel Seedat, Mihaela van der Schaar, Andrija Petrovic
Reimagining Synthetic Tabular Data Generation through Data-Centric AI: A Comprehensive Benchmark. CoRR (2023)
Boris van Breugel, Nabeel Seedat, Fergus Imrie, Mihaela van der Schaar
Can You Rely on Your Model Evaluation? Improving Model Evaluation with Synthetic Test Data. NeurIPS (2023)
Elisabeth R. M. Heremans, Nabeel Seedat, Bertien Buyse, Dries Testelmans, Mihaela van der Schaar, Maarten De Vos
U-PASS: an Uncertainty-guided deep learning Pipeline for Automated Sleep Staging. CoRR (2023)
Nabeel Seedat, Jonathan Crabbé, Zhaozhi Qian, Mihaela van der Schaar
TRIAGE: Characterizing and auditing training data for improved regression. NeurIPS (2023)
Boris van Breugel, Nabeel Seedat, Fergus Imrie, Mihaela van der Schaar
Can You Rely on Your Model Evaluation? Improving Model Evaluation with Synthetic Test Data. CoRR (2023)
Hao Sun, Boris van Breugel, Jonathan Crabbé, Nabeel Seedat, Mihaela van der Schaar
What is Flagged in Uncertainty Quantification? Latent Density Models for Uncertainty Categorization. NeurIPS (2023)
Jeroen Berrevoets, Nabeel Seedat, Fergus Imrie, Mihaela van der Schaar
Differentiable and Transportable Structure Learning. ICML (2023)
Nabeel Seedat, Alan Jeffares, Fergus Imrie, Mihaela van der Schaar
Improving Adaptive Conformal Prediction Using Self-Supervised Learning. CoRR (2023)
Nabeel Seedat, Jonathan Crabbé, Zhaozhi Qian, Mihaela van der Schaar
TRIAGE: Characterizing and auditing training data for improved regression. CoRR (2023)
Lasse Hansen, Nabeel Seedat, Mihaela van der Schaar, Andrija Petrovic
Reimagining Synthetic Tabular Data Generation through Data-Centric AI: A Comprehensive Benchmark. NeurIPS (2023)
Nabeel Seedat, Nicolas Huynh, Boris van Breugel, Mihaela van der Schaar
Curated LLM: Synergy of LLMs and Data Curation for tabular augmentation in ultra low-data regimes. CoRR (2023)
Nabeel Seedat, Alan Jeffares, Fergus Imrie, Mihaela van der Schaar
Improving Adaptive Conformal Prediction Using Self-Supervised Learning. AISTATS (2023)
Hao Sun, Alex J. Chan, Nabeel Seedat, Alihan Hüyük, Mihaela van der Schaar
When is Off-Policy Evaluation Useful? A Data-Centric Perspective. CoRR (2023)
Jeroen Berrevoets, Nabeel Seedat, Fergus Imrie, Mihaela van der Schaar
Differentiable and Transportable Structure Learning. CoRR (2022)
Hongshu Liu, Nabeel Seedat, Julia Ive
Modeling Disagreement in Automatic Data Labelling for Semi-Supervised Learning in Clinical Natural Language Processing. CoRR (2022)
Nabeel Seedat, Jonathan Crabbé, Mihaela van der Schaar
Data-SUITE: Data-centric identification of in-distribution incongruous examples. ICML (2022)
Nabeel Seedat, Fergus Imrie, Alexis Bellot, Zhaozhi Qian, Mihaela van der Schaar
Continuous-Time Modeling of Counterfactual Outcomes Using Neural Controlled Differential Equations. CoRR (2022)
Nabeel Seedat, Jonathan Crabbé, Ioana Bica, Mihaela van der Schaar
Data-IQ: Characterizing subgroups with heterogeneous outcomes in tabular data. NeurIPS (2022)
Hao Sun, Boris van Breugel, Jonathan Crabbé, Nabeel Seedat, Mihaela van der Schaar
DAUX: a Density-based Approach for Uncertainty eXplanations. CoRR (2022)
Nabeel Seedat, Fergus Imrie, Mihaela van der Schaar
DC-Check: A Data-Centric AI checklist to guide the development of reliable machine learning systems. CoRR (2022)
Nabeel Seedat, Jonathan Crabbé, Mihaela van der Schaar
Data-SUITE: Data-centric identification of in-distribution incongruous examples. CoRR (2022)
Nabeel Seedat, Fergus Imrie, Alexis Bellot, Zhaozhi Qian, Mihaela van der Schaar
Continuous-Time Modeling of Counterfactual Outcomes Using Neural Controlled Differential Equations. ICML (2022)
Nabeel Seedat, Jonathan Crabbé, Ioana Bica, Mihaela van der Schaar
Data-IQ: Characterizing subgroups with heterogeneous outcomes in tabular data. CoRR (2022)
Nabeel Seedat
MCU-Net: A framework towards uncertainty representations for decision support system patient referrals in healthcare contexts. CoRR (2020)
Nabeel Seedat, Vered Aharonson, Ilana Schlesinger
Automated machine vision enabled detection of movement disorders from hand drawn spirals. ICHI (2020)
Nabeel Seedat, Vered Aharonson
Machine learning discrimination of Parkinson's Disease stages from walker-mounted sensors data. CoRR (2020)
Nabeel Seedat, Vered Aharonson, Ilana Schlesinger
Automated machine vision enabled detection of movement disorders from hand drawn spirals. CoRR (2020)
Nabeel Seedat, Christopher Kanan
Towards calibrated and scalable uncertainty representations for neural networks. CoRR (2019)
Nabeel Seedat, Irfaan Mohamed, Abdul-Khaaliq Mohamed
Custom Force Sensor and Sensory Feedback System to Enable Grip Control of a Robotic Prosthetic Hand. BioRob (2018)