NAM: Normalization-based Attention Module
Liu, Y., Shao, Z., Teng, Y., Hoffmann N. (2021). NAM: Normalization-based Attention Module. ImageNet PPF @ NeurIPS 2021.
CV
Education
- B.S. in GitHub, GitHub University, 2012
- M.S. in Jekyll, GitHub University, 2014
- Ph.D in Version Control Theory, GitHub University, 2018 (expected)
Work experience
- Summer 2015: Research Assistant
- Github University
- Duties included: Tagging issues
- Supervisor: Professor Git
- Fall 2015: Research Assistant
- Github University
- Duties included: Merging pull requests
- Supervisor: Professor Hub
Skills
- Skill 1
- Skill 2
- Sub-skill 2.1
- Sub-skill 2.2
- Sub-skill 2.3
- Skill 3
Publications
Data-Driven Shadowgraph Simulation of a 3D Object
Willmann, A., Stiller, P., Debus, A., Irman, A., Pausch, R., Chang, Y.-Y.,Bussmann, M., Hoffmann, N. (2021). Data-Driven Shadowgraph Simulation of a 3D Object. Simulation with Deep Learning @ ICLR.
Invertible Surrogate Models: Joint Surrogate Modelling and Reconstruction of Laser Wakefield Acceleration by Invertible Neural Networks
Bethke, F., Pausch, R., Stiller, P., Debus, A., Bussmann, M., Hoffmann, N. (2021). Invertible Surrogate Models: Joint Surrogate Modelling and Reconstruction of Laser Wakefield Acceleration by Invertible Neural Networks. Simulation with Deep Learning @ ICLR.
Investigating Brain Connectivity with Graph Neural Networks and GNNExplainer
Zhdanov, M., Steinmann, S., Hoffmann N. (2022). Investigating Brain Connectivity with Graph Neural Networks and GNNExplainer. ICPR 2022.
Learning Electron Bunch Distribution along a FEL Beamline by Normalising Flows
Willmann A.,Cabadag J.C.,Chang Y.-Y.,Pausch R.,Ghaith A.,Debus A.,Irman A., Bussmann M., Schramm U., Hoffmann N. (2022). Learning Electron Bunch Distribution along a FEL Beamline by Normalising Flows. Machine Learning and the Physical Sciences @ NeurIPS 2022.
Amortized Bayesian Inference of GISAXS Data with Normalizing Flows
Zhdanov, M., Randolph, L., Kluge, T., Nakatsutsumi, M., Gutt, C., Ganeva, M., Hoffmann, N. (2022). Amortized Bayesian Inference of GISAXS Data with Normalizing Flows. Machine Learning and the Physical Sciences @ NeurIPS 2022.
Continual learning autoencoder training for a particle-in-cell simulation via streaming
Stiller P., Makdani V., Pöschel F. , Richard P., Debus A., Bussmann M., Hoffmann N. (2022). Continual learning autoencoder training for a particle-in-cell simulation via streaming. Machine Learning and the Physical Sciences workshop @ NeurIPS 2022.
Talks
Talk 1 on Relevant Topic in Your Field
Talk at UC San Francisco, Department of Testing, San Francisco, California
Tutorial 1 on Relevant Topic in Your Field
Tutorial at UC-Berkeley Institute for Testing Science, Berkeley CA, USA
Talk 2 on Relevant Topic in Your Field
Talk at London School of Testing, London, UK
Conference Proceeding talk 3 on Relevant Topic in Your Field
Conference proceedings talk at Testing Institute of America 2014 Annual Conference, Los Angeles, CA
Teaching
Service and leadership
- Currently signed in to 43 different slack teams