Large-Scale Visual Active Learning with Deep Probabilistic Ensembles K Chitta, JM Alvarez, A Lesnikowski arXiv preprint arXiv:1811.03575, 2018 | 33 | 2018 |
The Relevance of Bayesian Layer Positioning to Model Uncertainty in Deep Bayesian Active Learning J Zeng, A Lesnikowski, JM Alvarez Third workshop on Bayesian Deep Learning, NeurIPS 2018, 2018 | 25 | 2018 |
Unsupervised Distribution Learning for Lunar Surface Anomaly Detection A Lesnikowski, VT Bickel, D Angerhausen Second Workshop on Machine Learning and the Physical Sciences, NeurIPS 2019, 2019 | 12 | 2019 |
Synthetic Data and Simulators for Recommendation Systems: Current State and Future Directions A Lesnikowski, GSP Moreira, S Rabhi, K Byleen-Higley SimuRec 2021: Workshop on Simulation Methods for Recommender Systems at ACM …, 2021 | 2 | 2021 |
Deep Probabilistic Ensembles: Approximate Variational Inference through KL Regularization K Chitta, JM Alvarez, A Lesnikowski Third workshop on Bayesian Deep Learning, NeurIPS 2018, 2018 | 2 | 2018 |
Neural Anomaly Search on Lunar Reconnaissance Orbiter Camera Images A Lesnikowski, VT Bickel, D Angerhausen, D Singh Chauhan, ... The Astrobiology Science Conference (AbSciCon) 2022, 301-05, 2022 | 1 | 2022 |
Automated Discovery of Anomalous Features in Ultra-Large Planetary Remote Sensing Datasets using Variational Autoencoders A Lesnikowski, VT Bickel, D Angerhausen IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2024 | | 2024 |