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Maja Rudolph
Maja Rudolph
Lead Research Scientist, Bosch Center for AI
Bestätigte E-Mail-Adresse bei cs.columbia.edu - Startseite
Titel
Zitiert von
Zitiert von
Jahr
Edward: A library for probabilistic modeling, inference, and criticism
D Tran, A Kucukelbir, AB Dieng, M Rudolph, D Liang, DM Blei
arXiv preprint arXiv:1610.09787, 2016
3612016
Dynamic embeddings for language evolution
M Rudolph, D Blei
Proceedings of the 2018 World Wide Web Conference, 1003-1011, 2018
1822018
Exponential family embeddings
M Rudolph, F Ruiz, S Mandt, D Blei
Neural Information Processing Systems, 2016
1572016
Neural Transformation Learning for Deep Anomaly Detection Beyond Images
C Qiu, T Pfrommer, M Kloft, S Mandt, M Rudolph
ICML 2021, 2021
1142021
Placing language in an integrated understanding system: Next steps toward human-level performance in neural language models
JL McClelland, F Hill, M Rudolph, J Baldridge, H Schütze
Proceedings of the National Academy of Sciences 117 (42), 25966-25974, 2020
942020
Modeling irregular time series with continuous recurrent units
M Schirmer, M Eltayeb, S Lessmann, M Rudolph
International Conference on Machine Learning, 19388-19405, 2022
592022
Structured embedding models for grouped data
M Rudolph, F Ruiz, S Athey, D Blei
Neural Information Processing Systems, 2017
512017
Latent outlier exposure for anomaly detection with contaminated data
C Qiu, A Li, M Kloft, M Rudolph, S Mandt
International conference on machine learning, 18153-18167, 2022
432022
Extending machine language models toward human-level language understanding
JL McClelland, F Hill, M Rudolph, J Baldridge, H Schütze
arXiv preprint arXiv:1912.05877, 2019
422019
Dynamic Bernoulli embeddings for language evolution
M Rudolph, D Blei
arXiv preprint arXiv:1703.08052, 2017
402017
Raising the Bar in Graph-level Anomaly Detection
C Qiu, M Kloft, S Mandt, M Rudolph
IJCAI 2022, 2022
352022
Complex-valued autoencoders for object discovery
S Löwe, P Lippe, M Rudolph, M Welling
arXiv preprint arXiv:2204.02075, 2022
282022
Objective variables for probabilistic revenue maximization in second-price auctions with reserve
MR Rudolph, JG Ellis, DM Blei
Proceedings of the 25th International Conference on World Wide Web, 1113-1122, 2016
222016
Detecting anomalies within time series using local neural transformations
T Schneider, C Qiu, M Kloft, DA Latif, S Staab, S Mandt, M Rudolph
arXiv preprint arXiv:2202.03944, 2022
162022
Timesead: Benchmarking deep multivariate time-series anomaly detection
D Wagner, T Michels, FCF Schulz, A Nair, M Rudolph, M Kloft
Transactions on Machine Learning Research, 2023
142023
Lora ensembles for large language model fine-tuning
X Wang, L Aitchison, M Rudolph
arXiv preprint arXiv:2310.00035, 2023
102023
Edward: A library for probabilistic modeling, inference, and criticism. arXiv 2016
D Tran, A Kucukelbir, AB Dieng, M Rudolph, D Liang, DM Blei
arXiv preprint arXiv:1610.09787, 2016
102016
Deep anomaly detection under labeling budget constraints
A Li, C Qiu, M Kloft, P Smyth, S Mandt, M Rudolph
International Conference on Machine Learning, 19882-19910, 2023
92023
Zero-shot anomaly detection via batch normalization
A Li, C Qiu, M Kloft, P Smyth, M Rudolph, S Mandt
Advances in Neural Information Processing Systems 36, 2024
62024
Deep anomaly detection on tennessee eastman process data
F Hartung, BJ Franks, T Michels, D Wagner, P Liznerski, S Reithermann, ...
Chemie Ingenieur Technik 95 (7), 1077-1082, 2023
42023
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