Name: First MODE Workshop on Differentiable Programming
Start: 2021-09-06T12:00:00+02:00
End: 2021-09-08T17:35:00+02:00
Location: CP3, Louvain-la-Neuve

First MODE Workshop on Differentiable Programming

from Monday, 6 September 2021 (12:00) to Wednesday, 8 September 2021 (17:35)

Monday, 6 September 2021

12:00

12:00 - 12:30
Room: Auditorium CYCL-01

12:30 Welcome Lunch
Welcome Lunch
12:30 - 13:30
Room: Auditorium CYCL-01

13:30 Introduction and goals of the Workshop
Introduction and goals of the Workshop
13:30 - 13:55
Room: Auditorium CYCL-01
13:55 Keynote Session: Differentiable Programming and Deep Learning
Keynote Session: Differentiable Programming and Deep Learning
13:55 - 16:55
Room: Auditorium CYCL-01
Contributions

13:55 Opening Lecture: Differentiable programming and design optimization - Atılım Güneş Baydin (University of Oxford)

14:55 Keynote Lecture: JAX for scientific computing - Adam Paszke (Google Brain)

15:55 Keynote Lecture: Generalization Properties of Deep Neural Networks Through The Prism of Interpolation - Mikhail Belkin (Halicioğlu Data Science Institute, UCSD)
16:55 Coffee Break
Coffee Break
16:55 - 17:25
Room: Auditorium CYCL-01
17:25 Applications in Muon Tomography
Applications in Muon Tomography
17:25 - 19:20
Room: Auditorium CYCL-01
Contributions

17:25 Machine Learning application to volcano eruption forecasting using muography - Laszlo Olah (Hungarian Academy of Sciences (HU))

17:50 Role of AI in the industrial applications of muon tomography - Pablo Martinez Ruiz Del Arbol (Universidad de Cantabria and CSIC (ES))

18:15 Material identification in nuclear waste drums using muon scattering tomography and multivariate analysis - Patrick Stowell (University of Sheffield)

18:40 TomOpt: PyTorch-based Differential Muon Tomography Optimisation - Giles Chatham Strong (Universita e INFN, Padova (IT))
Tuesday, 7 September 2021
09:00 Applications in Particle Physics
Applications in Particle Physics
09:00 - 11:10
Room: Auditorium CYCL-01
Contributions

09:00 Optimization of LHCb calorimeter - Alexey Boldyrev (NRU Higher School of Economics (Moscow, Russia))

09:25 CMS Open data application of INFERNO - Lukas Layer (Universita e INFN, Padova (IT))

09:50 Automatic Differentiation for error analysis in lattice QCD - Alberto Ramos Martinez (Univ. of Valencia and CSIC (ES))

10:15 Optimization of HEP accelerators - Auralee Linscott Edelen

10:40 Generation of Calorimeter Showers with Normalizing Flows: CaloFlow - Claudius Krause (Rutgers University)
11:15 Coffee Break
Coffee Break
11:15 - 11:35
Room: Auditorium CYCL-01
11:35
11:35 - 13:40
Room: Auditorium CYCL-01
Contributions

11:35 DNN for distortion fluctuation calibration of ALICE TPC - Maja Kabus (Warsaw University of Technology (PL))

12:00 Neural networks for jet-energy subtraction in heavy-ion collisions - Laura Brittany Havener (Yale University (US))

12:25 Deep learning stochastic processes with QCD phase transition - Lingxiao Wang (Frankfurt Institute for Advanced Studies)

12:50 Machine Learning Applications for CBM at FAIR - Shahid Khan (University of Tuebingen)

13:15 In-medium heavy-quark interaction via deep learning - Shuzhe SHI (McGill University)
13:40 Lunch
Lunch
13:40 - 14:30
Room: Auditorium CYCL-01
14:30
14:30 - 16:35
Room: Auditorium CYCL-01
Contributions

14:30 Cosmology in the machine learning era - Francisco Villaescusa-Navarro (OATS-INAF)

14:55 Gravitational Waves Detectors - Mateusz Bawaj (Università degli Studi di Perugia)

15:20 Optimization of Optical and Radio Detectors for high-energy Neutrinos - Christian Glaser (RWTH Aachen)

15:45 Targeted dark matter substructure inference with differentiable strong lensing - Adam Coogan (University of Amsterdam)

16:10 Cherenkov Telescopes - Gernot Maier
16:35 Coffee Break and group photo
Coffee Break and group photo
16:35 - 17:00
Room: Auditorium CYCL-01
17:00
17:00 - 19:25
Room: Auditorium CYCL-01
Contributions

17:00 AI In Neutrinoless Double Beta Decay Searches - Corey Adams (Argonne National Laboratory)

17:25 Machine Learning Techniques for Water Cherenkov Event Reconstruction - Nick Prouse (Queen Mary University of London)

17:50 Scalable, End-to-End, Deep-Learning-Based Data Reconstruction Chain for 3D Particle Imaging Detectors - François Drielsma (Universite de Geneve (CH))

18:15 Dark matter and its ML-enhanced direct detection - Christopher Tunnell (Rice University)

18:40 P-ONE: Test Case for ML Based Detector Design - Christian Haack (III. Physikalisches Institut B, RWTH Aachen University)

19:05 GENETIS: Evolving Antennas for Ultra-High Energy Neutrino Detection - Alexander Machtay (Ohio State University)
20:00 Social Dinner
Social Dinner
20:00 - 22:00
Room: Auditorium CYCL-01
Wednesday, 8 September 2021

10:00

10:00 - 11:00
Room: Auditorium CYCL-01

11:00 Coffee Break
Coffee Break
11:00 - 11:30
Room: Auditorium CYCL-01

11:30 (continued)
(continued)
11:30 - 13:30
Room: Auditorium CYCL-01

13:30 Lunch
Lunch
13:30 - 14:30
Room: Auditorium CYCL-01
14:30
14:30 - 15:20
Room: Auditorium CYCL-01
Contributions

14:30 Gradient-based probabilistic inference in Pyro.ai - Fritz Obermeyer (Broad Institute)

14:55 Efficient and modular implicit differentiation - Mathieu Blondel (Google Brain)
15:20 Coffee Break
Coffee Break
15:20 - 15:50
Room: Auditorium CYCL-01
15:50 (continued)
(continued)
15:50 - 17:05
Room: Auditorium CYCL-01
Contributions

15:50 Neos: upstream optimization for downstream inference - Nathan Daniel Simpson (Lund University (SE))

16:15 CERN GRID on Kubernetes - Lukas Alexander Heinrich (CERN)

16:40 Quantum Machine Learning - Su Yeon Chang (EPFL - Ecole Polytechnique Federale Lausanne (CH))
17:05

17:05 - 17:35
Room: Auditorium CYCL-01