research
∙
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 ...
share
research
∙
07/15/2022
A Probabilistic Autoencoder for Type Ia Supernovae Spectral Time Series
We construct a physically-parameterized probabilistic autoencoder (PAE) ...
research
∙
10/25/2021
Self-supervised similarity search for large scientific datasets
We present the use of self-supervised learning to explore and exploit la...
research
∙
09/30/2021
Mining for strong gravitational lenses with self-supervised learning
We employ self-supervised representation learning to distill information...
research
∙
01/12/2021
Estimating Galactic Distances From Images Using Self-supervised Representation Learning
We use a contrastive self-supervised learning framework to estimate dist...
research
∙
12/24/2020
Self-Supervised Representation Learning for Astronomical Images
Sky surveys are the largest data generators in astronomy, making automat...
research
∙
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...
research
∙
05/11/2018