Emily Fertig

Publication Activity (10 Years)

Years Active: 2012-2022
Publications (10 Years): 9

Top Topics

Probabilistic Modeling

High Compression

Variational Inference

Label Information

Top Venues

Publications

Gianluigi Silvestri, Emily Fertig, Dave Moore, Luca Ambrogioni
Embedded-model flows: Combining the inductive biases of model-free deep learning and explicit probabilistic modeling. ICLR (2022)
Gianluigi Silvestri, Emily Fertig, Dave Moore, Luca Ambrogioni
Embedded-model flows: Combining the inductive biases of model-free deep learning and explicit probabilistic modeling. CoRR (2021)
Luca Ambrogioni, Kate Lin, Emily Fertig, Sharad Vikram, Max Hinne, Dave Moore, Marcel van Gerven
Automatic structured variational inference. AISTATS (2021)
Jasper Snoek, Yaniv Ovadia, Emily Fertig, Balaji Lakshminarayanan, Sebastian Nowozin, D. Sculley, Joshua V. Dillon, Jie Ren, Zachary Nado
Can you trust your model's uncertainty? Evaluating predictive uncertainty under dataset shift. NeurIPS (2019)
Jie Ren, Peter J. Liu, Emily Fertig, Jasper Snoek, Ryan Poplin, Mark A. DePristo, Joshua V. Dillon, Balaji Lakshminarayanan
Likelihood Ratios for Out-of-Distribution Detection. CoRR (2019)
Yaniv Ovadia, Emily Fertig, Jie Ren, Zachary Nado, David Sculley, Sebastian Nowozin, Joshua V. Dillon, Balaji Lakshminarayanan, Jasper Snoek
Can You Trust Your Model's Uncertainty? Evaluating Predictive Uncertainty Under Dataset Shift. CoRR (2019)
Bryan Seybold, Emily Fertig, Alex Alemi, Ian Fischer
Dueling Decoders: Regularizing Variational Autoencoder Latent Spaces. CoRR (2019)
Jie Ren, Peter J. Liu, Emily Fertig, Jasper Snoek, Ryan Poplin, Mark A. DePristo, Joshua V. Dillon, Balaji Lakshminarayanan
Likelihood Ratios for Out-of-Distribution Detection. NeurIPS (2019)
Emily Fertig, Aryan Arbabi, Alexander A. Alemi
β-VAEs can retain label information even at high compression. CoRR (2018)
Jay Apt, Emily Fertig, Warren Katzenstein
Smart Integration of Variable and Intermittent Renewables. HICSS (2012)