Name: Accelerating the Search for Dark Matter with Machine Learning
Start: 2018-01-15T09:00:00+01:00
End: 2018-01-19T14:45:00+01:00
Location: Lorentz Center@Oort

Adversarial Games for Particle Physics

Arrival / Registration

Astronomical Dark Matter measurements and Challenges

BSM-AI (SUSY-AI) and iDarkSurvey: Learning (from) high-dimensional models

Characterization of the Local Universe via angular cross-correlations

Cross link: Deep Learning in High Energy Physics

Dark Matter model exploration and first ML ideas

Dark Matter overview

Dark matter searches in dwarf irregular galaxies

Data-driven constraints on dark matter from dwarf galaxies

Discussion Unsupervised Leaning for Dark Matter

Discussion: First connections ?

Discussion: Further ideas?

Discussion: New ideas ?

Discussion: New ideas?

Discussion: New ideas? Reinforcement Learning?

Estimating the parameters of gravitational lenses with deep learning

Fast Forecasting for Counting Experiments

Fast model discrimination with Euclideanized signals

First ideas to connect Astronomical data, Deep Learning and Image Analysis

First ideas to use Machine Learning in direct Dark Matter searches

First ideas to use Machine Learning in indirect detection

First ideas: Supervised DNNs for reconstruction in LHC data

How to find Natural Supersymmetric Dark Matter?

Introduction into Deep Learning and Image Analysis

Introduction into direct and indirect Dark Matter searches and their challenges

Introduction into theory models for Dark Matter particles

Introduction into unsupervised learning

Machine Learning for SHiP and NEWS experiments

Miscellaneous thoughts on Machine Learning & Dark Matter

New approaches in semi-supervised learning

Open discussion: what have we leart? What next?

OpenML/AutoML: Organizing machine learning data and learning to learn better models

Recent results : Dark Matter searches at LHC

Results of yesterdays workgroups on Deep Learning, Image Analysis and astronomical Dark Matter data

Results of yesterdays workgroups on supervised learning and DM searches at the LHC

Results of yesterdays workgroups on unsupervised learning, direct and indirect DM searches

The hunt for stellar-mass DM clumps: applying the statistical machine learning techniques to strong microlensing events

Using Deep Learning to predict Electroweakino production cross-sections at the LHC

Welcome from Lorentz Center

Welcome, Workshop Structure and Objectives

Work in subgroups

Work in subgroups : Finding new projects in Deep Learning / Image Analysis

Work on projects in subgroups

Accelerating the Search for Dark Matter with Machine Learning

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Accelerating the Search for Dark Matter with Machine Learning

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