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06/07/2023
Exposing flaws of generative model evaluation metrics and their unfair treatment of diffusion models
We systematically study a wide variety of image-based generative models ...
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07/15/2022
A Probabilistic Autoencoder for Type Ia Supernovae Spectral Time Series
We construct a physically-parameterized probabilistic autoencoder (PAE) ...
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10/25/2021
Self-supervised similarity search for large scientific datasets
We present the use of self-supervised learning to explore and exploit la...
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09/30/2021
Mining for strong gravitational lenses with self-supervised learning
We employ self-supervised representation learning to distill information...
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01/12/2021
Estimating Galactic Distances From Images Using Self-supervised Representation Learning
We use a contrastive self-supervised learning framework to estimate dist...
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12/24/2020
Self-Supervised Representation Learning for Astronomical Images
Sky surveys are the largest data generators in astronomy, making automat...
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12/21/2020
Unsupervised in-distribution anomaly detection of new physics through conditional density estimation
Anomaly detection is a key application of machine learning, but is gener...
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05/11/2018
