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Researcher Evidence Record

Marvin Lerousseau

This bounded record lists 12 Pith paper rows and 0 imported work rows attributed to this corpus identity. The enumerated, non-disputed paper rows include cs.CV, eess.IV, cs.LG work dated 2019 to 2022. The record describes sources and coverage; it makes no judgment about the person.

Compiled coverage vector

Measured lane counts only. Not a trust score or person verdict.

Enumerated paper scope: 5 fields (cs.CV, eess.IV, cs.LG, +2 more) · 2019-2022 sources: authors, author_identifiers · paper_authors · author_works · current_verdicts · cited_works

A sourced case file for attributed work. It is neither a profile score nor a verdict about this researcher.

Attributed works

A bounded ledger from the Pith paper and imported-work queries. Counts and source confidence stay with each work.

  1. 2022 Pith paper

    Giga-SSL: Self-Supervised Learning for Gigapixel Images

    cs.CV provisional measured, no current review

    Sources and evidence
    Authorship source
    arxiv_oai
    Printed name
    Marvin Lerousseau
    Author position
    2
    Identity state
    provisional
    Source confidence
    0.7
    Review coverage
    Measured: no current Pith review exists.
    Citation counts
    No source count is attached to this work row.
  2. 2021 Pith paper

    MICS : Multi-steps, Inverse Consistency and Symmetric deep learning registration network

    cs.CV provisional measured, no current review

    Sources and evidence
    Authorship source
    arxiv_oai
    Printed name
    Marvin Lerousseau
    Author position
    5
    Identity state
    provisional
    Source confidence
    0.7
    Review coverage
    Measured: no current Pith review exists.
    Citation counts
    • 1 pith inbound references from cited_work_pith_inbound_counts
  3. 2021 Pith paper

    Exploring Deep Registration Latent Spaces

    cs.CV provisional measured, no current review

    Sources and evidence
    Authorship source
    arxiv_oai
    Printed name
    Marvin Lerousseau
    Author position
    6
    Identity state
    provisional
    Source confidence
    0.7
    Review coverage
    Measured: no current Pith review exists.
    Citation counts
    No source count is attached to this work row.
  4. 2021 Pith paper

    Weakly supervised pan-cancer segmentation tool

    eess.IV provisional measured, no current review

    Sources and evidence
    Authorship source
    arxiv_oai
    Printed name
    Marvin Lerousseau
    Author position
    1
    Identity state
    provisional
    Source confidence
    0.7
    Review coverage
    Measured: no current Pith review exists.
    Citation counts
    No source count is attached to this work row.
  5. 2021 Pith paper

    SparseConvMIL: Sparse Convolutional Context-Aware Multiple Instance Learning for Whole Slide Image Classification

    cs.CV provisional measured, no current review

    Sources and evidence
    Authorship source
    arxiv_oai
    Printed name
    Marvin Lerousseau
    Author position
    1
    Identity state
    provisional
    Source confidence
    0.7
    Review coverage
    Measured: no current Pith review exists.
    Citation counts
    No source count is attached to this work row.
  6. 2021 Pith paper

    Design and implementation of an environment for Learning to Run a Power Network (L2RPN)

    cs.LG provisional measured, no current review

    Sources and evidence
    Authorship source
    arxiv_oai
    Printed name
    Marvin Lerousseau
    Author position
    1
    Identity state
    provisional
    Source confidence
    0.7
    Review coverage
    Measured: no current Pith review exists.
    Citation counts
    No source count is attached to this work row.
  7. 2021 Pith paper

    Cancer Gene Profiling through Unsupervised Discovery

    q-bio.GN provisional measured, no current review

    Sources and evidence
    Authorship source
    arxiv_oai
    Printed name
    Marvin Lerousseau
    Author position
    5
    Identity state
    provisional
    Source confidence
    0.7
    Review coverage
    Measured: no current Pith review exists.
    Citation counts
    No source count is attached to this work row.
  8. 2020 Pith paper

    Brain tumor segmentation with self-ensembled, deeply-supervised 3D U-net neural networks: a BraTS 2020 challenge solution

    eess.IV provisional measured, no current review

    Sources and evidence
    Authorship source
    arxiv_oai
    Printed name
    Marvin Lerousseau
    Author position
    3
    Identity state
    provisional
    Source confidence
    0.7
    Review coverage
    Measured: no current Pith review exists.
    Citation counts
    • 1 pith inbound references from cited_work_pith_inbound_counts
  9. 2020 Pith paper

    Deep learning based registration using spatial gradients and noisy segmentation labels

    cs.CV provisional measured, no current review

    Sources and evidence
    Authorship source
    arxiv_oai
    Printed name
    Marvin Lerousseau
    Author position
    6
    Identity state
    provisional
    Source confidence
    0.7
    Review coverage
    Measured: no current Pith review exists.
    Citation counts
    No source count is attached to this work row.
  10. 2020 Pith paper

    Multimodal brain tumor classification

    eess.IV provisional measured, no current review

    Sources and evidence
    Authorship source
    arxiv_oai
    Printed name
    Marvin Lerousseau
    Author position
    1
    Identity state
    provisional
    Source confidence
    0.7
    Review coverage
    Measured: no current Pith review exists.
    Citation counts
    • 1 pith inbound references from cited_work_pith_inbound_counts
  11. 2020 Pith paper

    Weakly supervised multiple instance learning histopathological tumor segmentation

    eess.IV provisional measured, no current review

    Sources and evidence
    Authorship source
    arxiv_oai
    Printed name
    Marvin Lerousseau
    Author position
    1
    Identity state
    provisional
    Source confidence
    0.7
    Review coverage
    Measured: no current Pith review exists.
    Citation counts
    No source count is attached to this work row.
  12. 2019 Pith paper

    Learning to run a power network challenge for training topology controllers

    eess.SP provisional measured, no current review

    Sources and evidence
    Authorship source
    arxiv_oai
    Printed name
    Marvin Lerousseau
    Author position
    5
    Identity state
    provisional
    Source confidence
    0.7
    Review coverage
    Measured: no current Pith review exists.
    Citation counts
    • 1 pith inbound references from cited_work_pith_inbound_counts

Evidence apparatus

The machinery behind this record. Every lane states whether Pith measured it, did not query it, could not reach it, or withheld it.

LaneStateObservedBoundary and source
identity Measured 2 Canonical identity row plus public typed identifiers.
source=authors, author_identifiers
papers Measured 12 of 12 bounded rows Rows attributed to this author UUID in the Pith corpus.
source=paper_authors
works Measured zero 0 of 0 bounded rows Imported works not duplicated by the paper ledger.
source=author_works
reviews Measured zero 0 of 12 bounded rows Coverage count only. No review outcome is projected onto the person.
source=current_verdicts
citations Measured 4 of 12 bounded rows Counts remain itemized by work and source.
source=cited_works
coauthors Measured 32 of 12 bounded rows Shared-work edges from admitted paper rows.
source=paper_authors
account Unavailable No public count of 1 bounded rows Account metadata is separate from corpus evidence.
source=users.author_id
Public identity sources
  • name variant
    Marvin Lerousseau
    backfill
    confidence 0.6
Enumerated research scope

Fields and dates come only from enumerated, non-disputed Pith paper rows. They do not claim career completeness.

  • cs.CV5 rows
  • eess.IV4 rows
  • cs.LG1 rows
  • eess.SP1 rows
  • q-bio.GN1 rows
  • 20191 rows
  • 20204 rows
  • 20216 rows
  • 20221 rows
Shared-work index
Record scope

The work queries are bounded. Missing rows may mean measured zero, an unavailable source, a query that did not run, or private data that Pith withheld. The lane table keeps those cases separate.

Paper findings remain attached to papers. They do not become findings about this researcher.