עקוב אחר
Ghassen Jerfel
Ghassen Jerfel
Research @Waymo. Ex-Google Brain, UC Berkeley, Duke, Princeton.
כתובת אימייל מאומתת בדומיין alumni.princeton.edu - דף הבית
כותרת
צוטט על ידי
צוטט על ידי
שנה
Underspecification presents challenges for credibility in modern machine learning‏
A D'Amour, K Heller, D Moldovan, B Adlam, B Alipanahi, A Beutel, ...‏
Journal of Machine Learning Research 23 (226), 1-61, 2022‏
7482022
Measuring Calibration in Deep Learning.‏
J Nixon, MW Dusenberry, L Zhang, G Jerfel, D Tran‏
CVPR workshops 2 (7), 2019‏
4782019
Efficient and scalable bayesian neural nets with rank-1 factors‏
M Dusenberry, G Jerfel, Y Wen, Y Ma, J Snoek, K Heller, ...‏
International conference on machine learning, 2782-2792, 2020‏
2362020
Reconciling meta-learning and continual learning with online mixtures of tasks‏
G Jerfel, E Grant, T Griffiths, KA Heller‏
Advances in neural information processing systems 32, 2019‏
182*2019
Analyzing the role of model uncertainty for electronic health records‏
MW Dusenberry, D Tran, E Choi, J Kemp, J Nixon, G Jerfel, K Heller, ...‏
Proceedings of the ACM Conference on Health, Inference, and Learning, 204-213, 2020‏
1082020
Uncertainty baselines: Benchmarks for uncertainty & robustness in deep learning‏
Z Nado, N Band, M Collier, J Djolonga, MW Dusenberry, S Farquhar, ...‏
arXiv preprint arXiv:2106.04015, 2021‏
1072021
Combining ensembles and data augmentation can harm your calibration‏
Y Wen, G Jerfel, R Muller, MW Dusenberry, J Snoek, ...‏
arXiv preprint arXiv:2010.09875, 2020‏
672020
Benchmarking bayesian deep learning on diabetic retinopathy detection tasks‏
N Band, TGJ Rudner, Q Feng, A Filos, Z Nado, MW Dusenberry, G Jerfel, ...‏
arXiv preprint arXiv:2211.12717, 2022‏
492022
A simple approach to improve single-model deep uncertainty via distance-awareness‏
JZ Liu, S Padhy, J Ren, Z Lin, Y Wen, G Jerfel, Z Nado, J Snoek, D Tran, ...‏
Journal of Machine Learning Research 24 (42), 1-63, 2023‏
402023
Variational Refinement for Importance Sampling Using the Forward Kullback-Leibler Divergence‏
G Jerfel, SL Wang, C Fannjiang, KA Heller, Y Ma, M Jordan‏
Uncertainty in Artificial Intelligence, 2020‏
362020
Adanet: A scalable and flexible framework for automatically learning ensembles‏
C Weill, J Gonzalvo, V Kuznetsov, S Yang, S Yak, H Mazzawi, E Hotaj, ...‏
arXiv preprint arXiv:1905.00080, 2019‏
222019
Sparse MoEs meet efficient ensembles‏
JU Allingham, F Wenzel, ZE Mariet, B Mustafa, J Puigcerver, N Houlsby, ...‏
arXiv preprint arXiv:2110.03360, 2021‏
212021
Dynamic Collaborative Filtering with Compound Poisson Factorization‏
G Jerfel, ME Basbug, BE Engelhardt‏
Artificial Intelligence and Statistics (AISTATS 2017), 2016‏
152016
Deep uncertainty and the search for proteins‏
Z Mariet, G Jerfel, Z Wang, C Angermüller, D Belanger, S Vora, M Bileschi, ...‏
Workshop: Machine Learning for Molecules 196, 201, 2020‏
32020
Boosted Stochastic Backpropagation for Variational Inference‏
G Jerfel‏
Princeton University, 2017‏
22017
Multimodal Probabilistic Inference for Robust Uncertainty Quantification‏
G Jerfel‏
Duke University, 2021‏
12021
Ensembling mixture-of-experts neural networks‏
R Jenatton, CR Ruiz, D Tran, JU Allingham, F Wenzel, ZE Mariet, ...‏
US Patent App. 17/960,780, 2023‏
2023
Non-asymptotic Analysis of Langevin Monte Carlo Algorithms: A Review of Three Influential Papers‏
G Jerfel‏
2019
An Information Theoretic Interpretation of Variational Inference based on the MDL Principle and the Bits-Back Coding Scheme‏
G Jerfel‏
2017
המערכת אינה יכולה לבצע את הפעולה כעת. נסה שוב מאוחר יותר.
מאמרים 1–19