Name: Advanced Data Analysis Techniques
Start: 2022-02-04T08:30:00+00:00
End: 2022-02-04T13:25:00+00:00
Location: Dep. of Physics, FCTUC

Advanced Data Analysis Techniques

Friday, 4 February 2022 - 08:30

Monday, 31 January 2022
Tuesday, 1 February 2022
Wednesday, 2 February 2022
Thursday, 3 February 2022
Friday, 4 February 2022
08:30 Automatic Feature Extraction for Heartbeat Anomaly Detection - Beatriz Santos
Automatic Feature Extraction for Heartbeat Anomaly Detection
- Beatriz Santos
08:30 - 08:35
Room: D.14 https://arxiv.org/abs/2102.12289
08:40 Automatic Segmentation and Classification of Heart Sounds Using Modified Empirical Wavelet Transform and Power Features - Francisco Relvão
Automatic Segmentation and Classification of Heart Sounds Using Modified Empirical Wavelet Transform and Power Features
- Francisco Relvão
08:40 - 08:45
Room: D.14 https://www.mdpi.com/2076-3417/10/14/4791
08:50 Audio analysis: measuring heart rate and classifying heart sounds - Francisco Relvão Beatriz Santos
Audio analysis: measuring heart rate and classifying heart sounds
- Francisco Relvão
- Beatriz Santos
08:50 - 09:00
Room: D.14
09:05 Phonocardiographic Sensing using Deep Learning for Abnormal Heartbeat Detection - Sílvia Santos
Phonocardiographic Sensing using Deep Learning for Abnormal Heartbeat Detection
- Sílvia Santos
09:05 - 09:10
Room: D.14 https://arxiv.org/abs/1801.08322
09:15 Heartbeat Sound Signal Classification Using Deep Learning - Nicole Duarte
Heartbeat Sound Signal Classification Using Deep Learning
- Nicole Duarte
09:15 - 09:20
Room: D.14 https://www.mdpi.com/1424-8220/19/21/4819
09:25 Audio analysis: measuring heart rate and classifying heart sounds - Nicole Duarte Sílvia Santos
Audio analysis: measuring heart rate and classifying heart sounds
- Nicole Duarte
- Sílvia Santos
09:25 - 09:35
Room: D.14
09:40 Deep Learning for the Classification of Quenched Jets - Gonçalo Gouveia
Deep Learning for the Classification of Quenched Jets
- Gonçalo Gouveia
09:40 - 09:45
Room: D.14 https://arxiv.org/abs/2106.08869
09:50 Energy reconstruction in a liquid argon calorimeter cell using convolutional neural networks - António Caramelo
Energy reconstruction in a liquid argon calorimeter cell using convolutional neural networks
- António Caramelo
09:50 - 09:55
Room: D.14 https://arxiv.org/abs/2109.05124
10:00 Machine Learning for detector design, modelling the TileCal degradation history as a use case - Gonçalo Gouveia António Caramelo
Machine Learning for detector design, modelling the TileCal degradation history as a use case
- Gonçalo Gouveia
- António Caramelo
10:00 - 10:10
Room: D.14
10:15 On the Use of Neural Networks for Energy Reconstruction in High-granularity Calorimeters - Hugo Costa
On the Use of Neural Networks for Energy Reconstruction in High-granularity Calorimeters
- Hugo Costa
10:15 - 10:20
Room: D.14 https://arxiv.org/abs/2107.10207
10:25 Calorimetry with Deep Learning: Particle Simulation and Reconstruction for Collider Physics - Seomara Felix
Calorimetry with Deep Learning: Particle Simulation and Reconstruction for Collider Physics
- Seomara Felix
10:25 - 10:30
Room: D.14 https://arxiv.org/abs/1912.06794
10:35 Machine Learning for detector design, modelling the TileCal degradation history as a use case - Seomara Felix Hugo Costa
Machine Learning for detector design, modelling the TileCal degradation history as a use case
- Seomara Felix
- Hugo Costa
10:35 - 10:45
Room: D.14
10:50 Coffee break
Coffee break
10:50 - 11:05
Room: D.14
11:10 Compressing physics with an autoencoder: Creating an atomic species representation to improve machine learning models in the chemical sciences - Bernardo Martins
Compressing physics with an autoencoder: Creating an atomic species representation to improve machine learning models in the chemical sciences
- Bernardo Martins
11:10 - 11:15
Room: D.14 https://indico.lip.pt/event/1187/manage/timetable/#20220204
11:20 Machine learning modeling of superconducting critical temperature - Gonçalo Dias
Machine learning modeling of superconducting critical temperature
- Gonçalo Dias
11:20 - 11:25
Room: D.14 https://www.nature.com/articles/s41524-018-0085-8
11:30 Machine Learning in Material Science - Bernardo Martins
Machine Learning in Material Science
- Bernardo Martins
11:30 - 11:40
Room: D.14
11:45 Machine Learning in Material Science - Gonçalo Martins
Machine Learning in Material Science
- Gonçalo Martins
11:45 - 11:55
Room: D.14
12:00 Nuclear matter properties: Supervised Machine Learning Approach - Valéria Carvalho
Nuclear matter properties: Supervised Machine Learning Approach
- Valéria Carvalho
12:00 - 12:10
Room: D.14
12:15 Finding New Physics without learning about it: Anomaly Detection as a tool for Searches at Colliders - Patricia Ferreira
Finding New Physics without learning about it: Anomaly Detection as a tool for Searches at Colliders
- Patricia Ferreira
12:15 - 12:20
Room: D.14 https://arxiv.org/abs/2006.05432
12:25 Anomaly detection for ATLAS trigger processing - Patricia Ferreira
Anomaly detection for ATLAS trigger processing
- Patricia Ferreira
12:25 - 12:35
Room: D.14
12:40 The SAMME.C2 algorithm for severely imbalanced multi-class classification - João Silva
The SAMME.C2 algorithm for severely imbalanced multi-class classification
- João Silva
12:40 - 12:45
Room: D.14 https://arxiv.org/abs/2112.14868
12:50 Random decision forests - Jorge Silva
Random decision forests
- Jorge Silva
12:50 - 12:55
Room: D.14 https://ieeexplore.ieee.org/document/598994
13:00 Classification of pulses in the LUX-ZEPLIN dark matter detector - Jorge Silva João Silva
Classification of pulses in the LUX-ZEPLIN dark matter detector
- Jorge Silva
- João Silva
13:00 - 13:10
Room: D.14
13:15 Classification of pulses in the LUX-ZEPLIN dark matter detector - Helena Lessa Patricia Pesch
Classification of pulses in the LUX-ZEPLIN dark matter detector
- Helena Lessa
- Patricia Pesch
13:15 - 13:25
Room: D.14