Name: Fast Machine Learning for Science Workshop 2022
Start: 2022-10-03T09:00:00-05:00
End: 2022-10-06T12:30:00-05:00
Location: Southern Methodist University

A Deep Learning Approach to Particle Identification for the AMS Electromagnetic Calorimeter (in session "Contributed Talks")

A Machine Learning Software Infrastructure for Gravitational Wave Signal Discovery (in session "Contributed Talks")

A Normalized Autoencoder for LHC triggers (in session "Contributed Talks")

A novel ML-based method of primary vertex reconstruction in high pile-up condition (in session "Contributed Talks")

Accelerating JEDI-net for jet tagging on FPGAs (in session "Contributed Talks")

Application and Opportunities in Nuclear Physics

Application of deep learning to instability tracking using high-speed video cameras in magnetic confinement fusion (in session "Contributed Talks")

Applications and Opportunities at the Large Hadron Collider

Applications and Opportunities for Machine Controls

Applications and Opportunities in Fusion Systems

Applications and Opportunities in Neutrino and DM experiments

Autonomous experiments in scanning probe microscopy: opportunities for rapid inference and decision making

Autonomous real-time science-driven follow-up of survey transients (in session "Contributed Talks")

Benchmarking Fast ML systems

Beyond CMOS

CryoAI – Prototyping cryogenic chips for machine learning at 22nm (in session "Contributed Talks")

Data Driven Weather Forecasting with Rudimentary Observables (in session "Contributed Talks")

Deep Neural Network Algorithms in the CMS Level-1 Trigger (in session "Contributed Talks")

Demonstration of Machine Learning-assisted real-time noise regression in LIGO (in session "Contributed Talks")

Deployment of ML in changing environments (in session "Contributed Talks")

Design and first test results of a reconfigurable autoencoder on an ASIC for data compression at the HL-LHC (in session "Contributed Talks")

Designing intelligent DAQ systems for radiation instrumentation with hls4ml (in session "Contributed Talks")

Detection for Core-collapse Supernova and Fast Data Preprocessing (in session "Contributed Talks")

Efficient Computer Architectures

EMD Neural Network Loss for ECON-T ASIC Autoencoder (in session "Contributed Talks")

End-to-end acceleration of machine learning in gravitational wave physics (in session "Contributed Talks")

End-to-End Vertex Finding for the CMS Level-1 Trigger (in session "Contributed Talks")

Exa.TrkX inference as-a-service (in session "Contributed Talks")

Exploring FPGA in-storage computing for Supernova Burst detection in LArTPCs (in session "Contributed Talks")

Extremely Noisy 4D-TEM Strain Mapping Using Cycle Consistent Spatial Transforming Autoencoders (in session "Contributed Talks")

Fast recurrent neural networks on FPGAs with hls4ml (in session "Contributed Talks")

FastML Science Benchmarks: Accelerating Real-Time Scientific Edge Machine Learning (in session "Contributed Talks")

FKeras: A Fault Tolerance Library for DNNs (in session "Contributed Talks")

Harnessing ultrafast ML for new algorithms at the CMS L1 trigger (in session "Contributed Talks")

hls4ml community session

hls4ml tutorial

Implementation of a pattern recognition neural network for live reconstruction using AI processors (in session "Contributed Talks")

Implementing Deep Neural Network Algorithms inside the CMS Level-1 Trigger (in session "Contributed Talks")

In-Pixel AI: From Algorithm to Accelerator (in session "Contributed Talks")

In-System Parameter Update and I/O Capture for Machine Learning IP Cores (in session "Contributed Talks")

Increasing the LHC Computational Power by integrating GPUs as a service (in session "Contributed Talks")

Intelligent experiments through real-time AI: Fast Data Processing and Autonomous Detector Control for sPHENIX and future EIC detectors (in session "Contributed Talks")

Interaction Network Autoencoder in the Level-1 Trigger (in session "Contributed Talks")

Large CNN for HLS4ML and Deepcalo (in session "Contributed Talks")

Low-latency Calorimetry Clustering at the LHC with SPVCNN (in session "Contributed Talks")

Low-latency Noise Subtraction of Gravitational Wave Data by DeepClean (in session "Contributed Talks")

Machine Learning for Science

Neural network accelerator for quantum control (in session "Contributed Talks")

Neural Signal Compression System for a Seizure-Predicting Brain Implant in CMOS 28nm (in session "Contributed Talks")

Next Generation Coprocessors as a service (in session "Contributed Talks")

Online-compatible Unsupervised Non-resonant Anomaly Detection (in session "Contributed Talks")

Quantized Distilled Autoencoder Model on FPGA for Real-Time Crystal Structure Detection in 4D Scanning Transmission Electron Microscopy (in session "Contributed Talks")

Quantized Neural Networks on FPGAs using HAWQ-V3 and hl4ml (in session "Contributed Talks")

Quantized ONNX (QONNX) (in session "Contributed Talks")

Rapid Fitting of Band-Excitation Piezoresponse Force Microscopy Using Physics Constrained Unsupervised Neural Networks (in session "Contributed Talks")

Rapid Generation of Kilonova Light Curves Using Conditional Variational Autoencoder (in session "Contributed Talks")

Real-time image processing for high-resolution imaging detectors (in session "Contributed Talks")

Resource Efficient and Low Latency GNN-based Particle Tracking on FPGA (in session "Contributed Talks")

Robust anomaly detection using NuRD (in session "Contributed Talks")

Semi-supervised Graph Neural Networks for Pileup Noise Removal (in session "Contributed Talks")

Some current challenges in materials measurements: an industrial perspective

The need for low latency with billion-year old signals

Toward Real Time Decision-Making in Material Science Experiments

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Fast Machine Learning for Science Workshop 2022