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Researcher Evidence Record

Luca Biggio

This bounded record lists 16 Pith paper rows and 0 imported work rows attributed to this corpus identity. The enumerated, non-disputed paper rows include cs.LG, astro-ph.CO, cs.CV work dated 2021 to 2023. 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: 7 fields (cs.LG, astro-ph.CO, cs.CV, +4 more) · 2021-2023 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. 2023 Pith paper

    Harnessing Synthetic Datasets: The Role of Shape Bias in Deep Neural Network Generalization

    cs.CV provisional measured, no current review

    Sources and evidence
    Authorship source
    arxiv_oai
    Printed name
    Luca Biggio
    Author position
    3
    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. 2023 Pith paper

    Accelerating galaxy dynamical modeling using a neural network for joint lensing and kinematics analyses

    astro-ph.GA provisional measured, no current review

    Sources and evidence
    Authorship source
    arxiv_oai
    Printed name
    Luca Biggio
    Author position
    3
    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.
  3. 2023 Pith paper

    Gemtelligence: Accelerating Gemstone classification with Deep Learning

    cs.CV provisional measured, no current review

    Sources and evidence
    Authorship source
    arxiv_oai
    Printed name
    Luca Biggio
    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.
  4. 2023 Pith paper

    Dynamic Context Pruning for Efficient and Interpretable Autoregressive Transformers

    cs.CL provisional measured, no current review

    Sources and evidence
    Authorship source
    arxiv_oai
    Printed name
    Luca Biggio
    Author position
    3
    Identity state
    provisional
    Source confidence
    0.7
    Review coverage
    Measured: no current Pith review exists.
    Citation counts
    • 3 pith inbound references from cited_work_pith_inbound_counts
  5. 2023 Pith paper

    Uncertainty Quantification in Machine Learning for Engineering Design and Health Prognostics: A Tutorial

    cs.LG provisional measured, no current review

    Sources and evidence
    Authorship source
    arxiv_oai
    Printed name
    Luca Biggio
    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.
  6. 2023 Pith paper

    Controllable Neural Symbolic Regression

    cs.LG provisional measured, no current review

    Sources and evidence
    Authorship source
    arxiv_oai
    Printed name
    Luca Biggio
    Author position
    2
    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
  7. 2023 Pith paper

    An SDE for Modeling SAM: Theory and Insights

    cs.LG provisional measured, no current review

    Sources and evidence
    Authorship source
    arxiv_oai
    Printed name
    Luca Biggio
    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.
  8. 2022 Pith paper

    Cosmology from Galaxy Redshift Surveys with PointNet

    astro-ph.CO provisional measured, no current review

    Sources and evidence
    Authorship source
    arxiv_oai
    Printed name
    Luca Biggio
    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
  9. 2022 Pith paper

    Modeling lens potentials with continuous neural fields in galaxy-scale strong lenses

    astro-ph.IM provisional measured, no current review

    Sources and evidence
    Authorship source
    arxiv_oai
    Printed name
    Luca Biggio
    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.
  10. 2022 Pith paper

    Fast emulation of two-point angular statistics for photometric galaxy surveys

    astro-ph.CO provisional measured, no current review

    Sources and evidence
    Authorship source
    arxiv_oai
    Printed name
    Luca Biggio
    Author position
    2
    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. 2022 Pith paper

    Signal Propagation in Transformers: Theoretical Perspectives and the Role of Rank Collapse

    cs.LG provisional measured, no current review

    Sources and evidence
    Authorship source
    arxiv_oai
    Printed name
    Luca Biggio
    Author position
    3
    Identity state
    provisional
    Source confidence
    0.7
    Review coverage
    Measured: no current Pith review exists.
    Citation counts
    • 6 pith inbound references from cited_work_pith_inbound_counts
  12. 2022 Pith paper

    Dynaformer: A Deep Learning Model for Ageing-aware Battery Discharge Prediction

    cs.LG provisional measured, no current review

    Sources and evidence
    Authorship source
    arxiv_oai
    Printed name
    Luca Biggio
    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
  13. 2022 Pith paper

    FIGARO: Generating Symbolic Music with Fine-Grained Artistic Control

    cs.SD provisional measured, no current review

    Sources and evidence
    Authorship source
    arxiv_oai
    Printed name
    Luca Biggio
    Author position
    2
    Identity state
    provisional
    Source confidence
    0.7
    Review coverage
    Measured: no current Pith review exists.
    Citation counts
    • 2 pith inbound references from cited_work_pith_inbound_counts
  14. 2022 Pith paper

    On the effectiveness of Randomized Signatures as Reservoir for Learning Rough Dynamics

    cs.LG provisional measured, no current review

    Sources and evidence
    Authorship source
    arxiv_oai
    Printed name
    Luca Biggio
    Author position
    3
    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.
  15. 2021 Pith paper

    Neural Symbolic Regression that Scales

    cs.LG provisional measured, no current review

    Sources and evidence
    Authorship source
    arxiv_oai
    Printed name
    Luca Biggio
    Author position
    1
    Identity state
    provisional
    Source confidence
    0.7
    Review coverage
    Measured: no current Pith review exists.
    Citation counts
    • 27 external cited by from pith
    • 1 pith inbound references from cited_work_pith_inbound_counts
  16. 2021 Pith paper

    Uncertainty-aware Remaining Useful Life predictor

    cs.LG provisional measured, no current review

    Sources and evidence
    Authorship source
    arxiv_oai
    Printed name
    Luca Biggio
    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.

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 16 of 16 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 16 bounded rows Coverage count only. No review outcome is projected onto the person.
source=current_verdicts
citations Measured 8 of 16 bounded rows Counts remain itemized by work and source.
source=cited_works
coauthors Measured 50 of 16 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
    Luca Biggio
    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.LG8 rows
  • astro-ph.CO2 rows
  • cs.CV2 rows
  • astro-ph.GA1 rows
  • astro-ph.IM1 rows
  • cs.CL1 rows
  • cs.SD1 rows
  • 20212 rows
  • 20227 rows
  • 20237 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.