Type
Funder
Country
—
Documents
150
through any edge
Papers
0
authorship edges
Awards made
10
6 grant numbers
Named as funder
150
no grant number
Identifiers
Funding
Read from the funding tables, never from the document count — that count includes authorship, so it ranks institutions, not funders.
What International Business Machines Corporation has funded
10 awards under 6 distinct grant numbers, across 10 documents. A further 150 documents name it as a funder without a grant number — a weaker claim, counted separately.
Quantifying uncertainty in deep learning approaches to radio galaxy classificationgrant ST/P006795/1 · 2022-01-26Sources of Understanding in Supervised Machine Learning Modelsgrant 2019/07665-4 · 2022-03-30Improving quantum genetic optimization through granular computinggrant W2177387 · 2022-10-08Exploring a POS-based Two-stage Approach for Improving Low-Resource AMR-to-Text Generationgrant 2013/07375-0 · 2022-01-01A Robust Cold-Start Approach Using Phylogramgrant 2013/07375-0 · 2024-10-17A Simultaneous Discover-Identify Approach to Causal Inference in Linear Modelsgrant A1771928 · 2020-04-03openalex-w7160240211grant 2019/07665-4MultEval: Supporting Collaborative Alignment for LLM-as-a-Judge Evaluation Criteriagrant 2025 Ph.D. Fellowship · 2026-04-01Comparison of Cross-lingual Strategies for AMR-to-Brazilian Portuguese Generationgrant 2013/07375-0 · 2022-11-11Artificial Intelligence, Ethics and Public Policy— The Use of Facial Recognition Systems in Public Transport in the Largest Brazilian Citiesgrant 2019/07665-4 · 2022-01-01
10 of 160 funding edges