Sökresultat - "Krauthammer, Michael"

Towards Scalable and Cross-Lingual Specialist Language Models for Oncology

Rohanian, Morteza, Mehra, Tarun, Miglino, Nicola, Nooralahzadeh, Farhad, Krauthammer, Michael, Wicki, Andreas

Uncertainty Modeling in Multimodal Speech Analysis Across the Psychosis Spectrum

Rohanian, Morteza, Hüppi, Roya M., Nooralahzadeh, Farhad, Dannecker, Noemi, Pauli, Yves, Surbeck, Werner, Sommer, Iris, Hinzen, Wolfram, Langer, Nicolas, Krauthammer, Michael, Homan, Philipp

RadVLM: A Multitask Conversational Vision-Language Model for Radiology

Deperrois, Nicolas, Matsuo, Hidetoshi, Ruipérez-Campillo, Samuel, Vandenhirtz, Moritz, Laguna, Sonia, Ryser, Alain, Fujimoto, Koji, Nishio, Mizuho, Sutter, Thomas M., Vogt, Julia E., Kluckert, Jonas, Frauenfelder, Thomas, Blüthgen, Christian, Nooralahzadeh, Farhad, Krauthammer, Michael

A Variational Perspective on Generative Protein Fitness Optimization

Bogensperger, Lea, Narnhofer, Dominik, Allam, Ahmed, Schindler, Konrad, Krauthammer, Michael

TAMER: A Test-Time Adaptive MoE-Driven Framework for EHR Representation Learning

Zhu, Yinghao, Zheng, Xiaochen, Allam, Ahmed, Krauthammer, Michael

Simple Contrastive Representation Learning for Time Series Forecasting

Zheng, Xiaochen, Chen, Xingyu, Schurch, Manuel, Mollaysa, Amina, Allam, Ahmed, Krauthammer, Michael

ICASSP 2024 - 2024 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

Learning Personalized Treatment Decisions in Precision Medicine: Disentangling Treatment Assignment Bias in Counterfactual Outcome Prediction and Biomarker Identification

Vollenweider, Michael, Schürch, Manuel, Rohrer, Chiara, Gut, Gabriele, Krauthammer, Michael, Wicki, Andreas

Machine learning prediction of prime editing efficiency across diverse chromatin contexts

Mathis, Nicolas, Allam, Ahmed, Tálas, András, Kissling, Lucas, Benvenuto, Elena, Schmidheini, Lukas^{Aff1, Aff3}, Schep, Ruben^{Aff4, Aff5}, Damodharan, Tanav, Balázs, Zsolt, Janjuha, Sharan, Ioannidi, Eleonora I., Böck, Desirée, van Steensel, Bas^{Aff4, Aff5}, Krauthammer, Michael, Schwank, Gerald^{Aff1, IDs41587024022682_cor1}

Rethinking Molecular Design: Integrating Latent Variable and Auto-Regressive Models for Goal Directed Generation

Arthur-Loui, Heath, Mollaysa, Amina, Krauthammer, Michael

Semi-Supervised Generative Models for Disease Trajectories: A Case Study on Systemic Sclerosis

Trottet, Cécile, Schürch, Manuel, Allam, Ahmed, Barua, Imon, Petelytska, Liubov, Launay, David, Airò, Paolo, Bečvář, Radim, Denton, Christopher, Radic, Mislav, Distler, Oliver, Hoffmann-Vold, Anna-Maria, Krauthammer, Michael, collaborators, the EUSTAR

Clustering of Disease Trajectories with Explainable Machine Learning: A Case Study on Postoperative Delirium Phenotypes

Zheng, Xiaochen, Schürch, Manuel, Chen, Xingyu, Komninou, Maria Angeliki, Schüpbach, Reto, Allam, Ahmed, Bartussek, Jan, Krauthammer, Michael

Towards AI-Based Precision Oncology: A Machine Learning Framework for Personalized Counterfactual Treatment Suggestions based on Multi-Omics Data

Schürch, Manuel, Boos, Laura, Heinzelmann-Schwarz, Viola, Gut, Gabriele, Krauthammer, Michael, Wicki, Andreas, Consortium, Tumor Profiler

Effective genome editing with an enhanced ISDra2 TnpB system and deep learning-predicted ωRNAs

Marquart, Kim Fabiano^{Aff1, Aff2}, Mathis, Nicolas, Mollaysa, Amina, Müller, Saphira, Kissling, Lucas, Rothgangl, Tanja, Schmidheini, Lukas^{Aff1, Aff2}, Kulcsár, Péter István, Allam, Ahmed, Kaufmann, Masako M.^{Aff4, Aff5}, Matsushita, Mai, Haenggi, Tatjana, Cathomen, Toni^{Aff4, Aff6}, Kopf, Manfred, Krauthammer, Michael, Schwank, Gerald^{Aff1, IDs4159202402418z_cor16}

Modeling Complex Disease Trajectories using Deep Generative Models with Semi-Supervised Latent Processes

Trottet, Cécile, Schürch, Manuel, Allam, Ahmed, Barua, Imon, Petelytska, Liubov, Distler, Oliver, Hoffmann-Vold, Anna-Maria, Krauthammer, Michael, collaborators, the EUSTAR

Two-Stage Aggregation with Dynamic Local Attention for Irregular Time Series

Chen, Xingyu, Zheng, Xiaochen, Mollaysa, Amina, Schürch, Manuel, Allam, Ahmed, Krauthammer, Michael

Attention-based Multi-task Learning for Base Editor Outcome Prediction

Mollaysa, Amina, Allam, Ahmed, Krauthammer, Michael

Publisher Correction: Machine learning prediction of prime editing efficiency across diverse chromatin contexts

Mathis, Nicolas, Allam, Ahmed, Tálas, András, Kissling, Lucas, Benvenuto, Elena, Schmidheini, Lukas^{Aff1, Aff3}, Schep, Ruben^{Aff4, Aff5}, Damodharan, Tanav, Balázs, Zsolt, Janjuha, Sharan, Ioannidi, Eleonora I., Böck, Desirée, van Steensel, Bas^{Aff4, Aff5}, Krauthammer, Michael, Schwank, Gerald^{Aff1, IDs41587024023830_cor1}

Generating Personalized Insulin Treatments Strategies with Deep Conditional Generative Time Series Models

Schürch, Manuel, Li, Xiang, Allam, Ahmed, Rathmes, Giulia, Mollaysa, Amina, Cavelti-Weder, Claudia, Krauthammer, Michael

Lost in Anonymization - A Data Anonymization Reference Classification Merging Legal and Technical Considerations

Vokinger, Kerstin N., Stekhoven, Daniel J., Krauthammer, Michael

Boosting Radiology Report Generation by Infusing Comparison Prior

Kim, Sanghwan, Nooralahzadeh, Farhad, Rohanian, Morteza, Fujimoto, Koji, Nishio, Mizuho, Sakamoto, Ryo, Rinaldi, Fabio, Krauthammer, Michael