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--- hepsim:public [2024/09/06 01:19] – hepsim17
+++ hepsim:public [2025/04/18 13:21] (current) – [HepSim in public talks] hepsim17
@@ Line 67: / Line 67: @@
   * Machine learning could help reveal undiscovered particles within data from the Large Hadron Collider, 2024, April  [[https://www.anl.gov/article/machine-learning-could-help-reveal-undiscovered-particles-within-data-from-the-large-hadron-collider|ANL press release]] [[https://www.newswise.com/doescience/machine-learning-could-help-reveal-undiscovered-particles-within-data-from-the-large-hadron-collider|newswise]] [[https://phys.org/news/2024-04-machine-reveal-undiscovered-particles-large.html|Phys.Org]]
   * ADFilter - a web tool for anomaly detection using autoencoders based on deep unsupervised neural networks, ATL-COM-PHYS-2024-469, July 6, 2024, https://cds.cern.ch/record/2903181
+  * S.V. Chekanov, W. Islam, R. Zhang, N. Luongo, "ADFilter -- A Web Tool for New Physics Searches With Autoencoder-Based Anomaly Detection Using Deep Unsupervised Neural Networks", (September 2024) ANL-HEP-190964, arXiv:2409.03065 (https://arxiv.org/abs/2409.03065)
+  * S.V. Chekanov, S. Eno, S. Magill, C. Palmer, L. Wu, M.Y.Aamir. "Geant4 simulations of sampling and homogeneous hadronic calorimeters with dual readout for future colliders." Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment. NIMA (2025) 1072, pp 170200 https://authors.elsevier.com/a/1kQBJcPqbwU9E
+  * S.V.Chekanov, W.Islam, R.Zhang, N.luongo, "ADFilter —A Web Tool for New Physics Searches with Autoencoder-Based Anomaly Detection Using Deep Unsupervised Neural Networks", Information 2025, 16(4), 258; https://www.mdpi.com/2078-2489/16/4/258
 There are also several ATLAS papers and a number of supporting notes that used Monte Carlo files from the HEPSIM repository.
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   * S.Chekanov, HepSim Monte Carlo repository and integration of its software with key4hep, FCC Software Meeting, May 30, 2023, https://indico.cern.ch/event/1283173/,
   * S.Chekanov et al, Geant4 simulations of sampling and homogeneous hadronic calorimeters with dual readout for future colliders, 2nd Future circular collider workshop (FCC-ee), Boston, MIT, March 24-28, 2024, (https://indico.mit.edu/event/876/)
-  *  	S.Chekanov et al, ADFilter: Online tool for processing BSM models using trained deep learning autoencoder. ATLAS Machine Learning Workshop,  May 13-16 (2024). https://indico.cern.ch/event/1352459/overview (CERN).
+  *  S.Chekanov et al, ADFilter: Online tool for processing BSM models using trained deep learning autoencoder. ATLAS Machine Learning Workshop,  May 13-16 (2024). https://indico.cern.ch/event/1352459/overview (CERN).
-  * S.V. Chekanov, W. Islam, R. Zhang, N. Luongo, "ADFilter -- A Web Tool for New Physics Searches With Autoencoder-Based Anomaly Detection Using Deep Unsupervised Neural Networks", (September 2024) ANL-HEP-190964, arXiv:2409.03065 (https://arxiv.org/abs/2409.03065)
+  * S.Chekanov et al, The initial studies of tracking using the CLD detector for FCC-ee. The FCCee detector meeting, CERN, Sep 28,  2024 https://indico.cern.ch/event/1448441/
+  * S.Chekanov et all, "Tracking studies with the full simulation of the CLD detector concept and its future improvement", 3rd Annual US Higgs Factory Future Collider Meeting, April 14-17 (2025), Fermilab/ANL, USA, (https://indico.fnal.gov/event/67484/contributions/313366/)