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R. Torre

49 papers hereh-index 293.8k citations72 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • sole author4
  • first author1
  • middle author13
  • last author26

Across the 44 of 49 papers where every author was matched, so the position is known.

fields
  • hep-ph43
  • cs.DL2
  • hep-ex1
  • hep-th1
  • physics.acc-ph1
  • stat.ML1
same name
  • R. Torre — 9 papers, h 26
  • R. Torre — 6 papers, h 9
  • R. Torre — 3 papers, h 6
  • R. Torre — 1 paper, h 4

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
20092023
most citedFlavour anomalies after the RK∗​ measurement

316 citations · 2.2k across the 47 of their papers we have counts for

collaborators
Showing 2022Show all

4 papers · 1 filter

hep-ph2022★ 6 cited

The Role of Vector Boson Fusion in the Production of Heavy Vector Triplets at the LHC and HL-LHC

Michael J. Baker, Timothy Martonhelyi, Andrea Thamm +1

We clarify the role of vector boson fusion (VBF) in the production of heavy vector triplets at the LHC and the HL-LHC. We point out that the presence of VBF production leads to an…

hep-ph2022★ 8 cited

The physics case of a 3 TeV muon collider stage

Jorge De Blas, Dario Buttazzo, Rodolfo Capdevilla +131

In the path towards a muon collider with center of mass energy of 10 TeV or more, a stage at 3 TeV emerges as an appealing option. Reviewing the physics potential of such muon coll…

hep-ph2022

Muon Collider Physics Summary

Chiara Aimè, Aram Apyan, Mohammed Attia Mahmoud +122

The perspective of designing muon colliders with high energy and luminosity, which is being investigated by the International Muon Collider Collaboration, has triggered a growing i…

stat.ML2022★ 4 cited

Testing the boundaries: Normalizing Flows for higher dimensional data sets

Humberto Reyes-Gonzalez, Riccardo Torre

Normalizing Flows (NFs) are emerging as a powerful class of generative models, as they not only allow for efficient sampling, but also deliver, by construction, density estimation.…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.