PAUSE: Positive and Annealed Unlabeled Sentence Embedding. - Lele Cao; Emil Larsson; Vilhelm von Ehrenheim; Dhiana Deva Cavalcanti Rocha; Anna Martin; Sonja Horn (EMNLP (1), 2021)

Simulation-Informed Revenue Extrapolation with Confidence Estimate for Scaleup Companies Using Scarce Time-Series Data. - Lele Cao; Sonja Horn; Vilhelm von Ehrenheim; Richard Anselmo Stahl; Henrik Landgren (CIKM, 2022)

Using Deep Learning to Find the Next Unicorn: A Practical Synthesis. - Lele Cao; Vilhelm von Ehrenheim; Sebastian Krakowski; Xiaoxue Li; Alexandra Lutz (CoRR, 2022)

A Scalable and Adaptive System to Infer the Industry Sectors of Companies: Prompt + Model Tuning of Generative Language Models. - Lele Cao; Vilhelm von Ehrenheim; Astrid Berghult; Cecilia Henje; Richard Anselmo Stahl; Joar Wandborg; Sebastian Stan; Armin Catovic; Erik Ferm; Hannes Ingelhag (CoRR, 2023)

Sourcing Investment Targets for Venture and Growth Capital Using Multivariate Time Series Transformer. - Lele Cao; Gustaf Halvardsson; Andrew McCornack; Vilhelm von Ehrenheim; Pawel Andrzej Herman (CoRR, 2023)

Beyond Gut Feel: Using Time Series Transformers to Find Investment Gems. - Lele Cao; Gustaf Halvardsson; Andrew McCornack; Vilhelm von Ehrenheim; Pawel Andrzej Herman (ICANN (9), 2024)

Self-Supervised Learning of Time Series Representation via Diffusion Process and Imputation-Interpolation-Forecasting Mask. - Zineb Senane; Lele Cao; Valentin Leonhard Buchner; Yusuke Tashiro; Lei You 002; Pawel Andrzej Herman; Mats Nordahl; Ruibo Tu; Vilhelm von Ehrenheim (KDD, 2024)

Prompt Tuned Embedding Classification for Industry Sector Allocation. - Valentin Leonhard Buchner; Lele Cao; Jan-Christoph Kalo; Vilhelm von Ehrenheim (NAACL (Industry Track), 2024)

CompanyKG: A Large-Scale Heterogeneous Graph for Company Similarity Quantification. - Lele Cao; Vilhelm von Ehrenheim; Mark Granroth-Wilding; Richard Anselmo Stahl; Andrew McCornack; Armin Catovic; Dhiana Deva Cavalcanti Rocha (IEEE Trans. Big Data, 2025)