6 citations · 19 across the 7 of their papers we have counts for
7 papers
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 +7
The Private Equity (PE) firms operate investment funds by acquiring and managing companies to achieve a high return upon selling. Many PE funds are thematic, meaning investment pro…
CompanyKG: A Large-Scale Heterogeneous Graph for Company Similarity Quantification
Lele Cao, Vilhelm von Ehrenheim, Mark Granroth-Wilding +4
In the investment industry, it is often essential to carry out fine-grained company similarity quantification for a range of purposes, including market mapping, competitor analysis…
Using Deep Learning to Find the Next Unicorn: A Practical Synthesis
Lele Cao, Vilhelm von Ehrenheim, Sebastian Krakowski +2
Startups often represent newly established business models associated with disruptive innovation and high scalability. They are commonly regarded as powerful engines for economic a…
Simulation-Informed Revenue Extrapolation with Confidence Estimate for Scaleup Companies Using Scarce Time-Series Data
Lele Cao, Sonja Horn, Vilhelm von Ehrenheim +2
Investment professionals rely on extrapolating company revenue into the future (i.e. revenue forecast) to approximate the valuation of scaleups (private companies in a high-growth…
PAUSE: Positive and Annealed Unlabeled Sentence Embedding
Lele Cao, Emil Larsson, Vilhelm von Ehrenheim +3
Sentence embedding refers to a set of effective and versatile techniques for converting raw text into numerical vector representations that can be used in a wide range of natural l…
Simple, Scalable, and Stable Variational Deep Clustering
Lele Cao, Sahar Asadi, Wenfei Zhu +2
Deep clustering (DC) has become the state-of-the-art for unsupervised clustering. In principle, DC represents a variety of unsupervised methods that jointly learn the underlying cl…
Analyzing Linear Dynamical Systems: From Modeling to Coding and Learning
Wenbing Huang, Fuchun Sun, Lele Cao +1
Encoding time-series with Linear Dynamical Systems (LDSs) leads to rich models with applications ranging from dynamical texture recognition to video segmentation to name a few. In…