1 code implementation • 9 May 2024 • Zineb Senane, Lele Cao, Valentin Leonhard Buchner, Yusuke Tashiro, Lei You, Pawel Herman, Mats Nordahl, Ruibo Tu, Vilhelm von Ehrenheim
Time Series Representation Learning (TSRL) focuses on generating informative representations for various Time Series (TS) modeling tasks.
no code implementations • 22 Feb 2024 • Lele Cao, Valentin Buchner, Zineb Senane, Fangkai Yang
We propose GenCeption, a novel and annotation-free MLLM evaluation framework that merely requires unimodal data to assess inter-modality semantic coherence and inversely reflects the models' inclination to hallucinate.
no code implementations • 23 Jan 2024 • Lei You, Lele Cao, Mattias Nilsson
This paper extends the concept of CEs to a distributional context, broadening the scope from individual data points to entire input and output distributions, named Distributional Counterfactual Explanation (DCE).
no code implementations • 9 Oct 2023 • Yinfeng Yu, Changan Chen, Lele Cao, Fangkai Yang, Fuchun Sun
As humans, we hear sound every second of our life.
no code implementations • 28 Sep 2023 • Lele Cao, Gustaf Halvardsson, Andrew McCornack, Vilhelm von Ehrenheim, Pawel Herman
This paper addresses the growing application of data-driven approaches within the Private Equity (PE) industry, particularly in sourcing investment targets (i. e., companies) for Venture Capital (VC) and Growth Capital (GC).
1 code implementation • 21 Sep 2023 • Valentin Leonhard Buchner, Lele Cao, Jan-Christoph Kalo, Vilhelm von Ehrenheim
All limitations (a), (b), and (c) are addressed by replacing the PLM's language head with a classification head, which is referred to as Prompt Tuned Embedding Classification (PTEC).
1 code implementation • 18 Jun 2023 • Lele Cao, Vilhelm von Ehrenheim, Mark Granroth-Wilding, Richard Anselmo Stahl, Andrew McCornack, Armin Catovic, Dhiana Deva Cavacanti Rocha
To the best of our knowledge, CompanyKG is the first large-scale heterogeneous graph dataset originating from a real-world investment platform, tailored for quantifying inter-company similarity.
no code implementations • 5 Jun 2023 • Lele Cao, Vilhelm von Ehrenheim, Astrid Berghult, Cecilia Henje, Richard Anselmo Stahl, Joar Wandborg, Sebastian Stan, Armin Catovic, Erik Ferm, Hannes Ingelhag
The Private Equity (PE) firms operate investment funds by acquiring and managing companies to achieve a high return upon selling.
no code implementations • 18 Oct 2022 • Lele Cao, Vilhelm von Ehrenheim, Sebastian Krakowski, Xiaoxue Li, Alexandra Lutz
The objective is a) to obtain a thorough and in-depth understanding of the methodologies for startup evaluation using DL, and b) to distil valuable and actionable learning for practitioners.
no code implementations • 4 Oct 2022 • Yinfeng Yu, Lele Cao, Fuchun Sun, Xiaohong Liu, Liejun Wang
Audio-visual embodied navigation, as a hot research topic, aims training a robot to reach an audio target using egocentric visual (from the sensors mounted on the robot) and audio (emitted from the target) input.
2 code implementations • CVPR 2022 • Yikai Wang, TengQi Ye, Lele Cao, Wenbing Huang, Fuchun Sun, Fengxiang He, DaCheng Tao
Recently, there is a trend of leveraging multiple sources of input data, such as complementing the 3D point cloud with 2D images that often have richer color and fewer noises.
1 code implementation • 19 Aug 2022 • Lele Cao, Sonja Horn, Vilhelm von Ehrenheim, Richard Anselmo Stahl, Henrik Landgren
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 stage) and inform their investment decision.
11 code implementations • journal 2022 • Yikai Wang, Xinghao Chen, Lele Cao, Wenbing Huang, Fuchun Sun, Yunhe Wang
Many adaptations of transformers have emerged to address the single-modal vision tasks, where self-attention modules are stacked to handle input sources like images.
Ranked #1 on Semantic Segmentation on SUN-RGBD (using extra training data)
1 code implementation • EMNLP 2021 • Lele Cao, Emil Larsson, Vilhelm von Ehrenheim, Dhiana Deva Cavalcanti Rocha, Anna Martin, Sonja Horn
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 language processing (NLP) applications.
1 code implementation • 16 May 2020 • Lele Cao, Sahar Asadi, Wenfei Zhu, Christian Schmidli, Michael Sjöberg
We then choose to focus on variational deep clustering (VDC) methods, since they mostly meet those criteria except for simplicity, scalability, and stability.
no code implementations • 3 Aug 2016 • Wenbing Huang, Fuchun Sun, Lele Cao, Mehrtash Harandi
We then devise efficient algorithms to perform sparse coding and dictionary learning on the space of infinite-dimensional subspaces.
no code implementations • CVPR 2016 • Wenbing Huang, Fuchun Sun, Lele Cao, Deli Zhao, Huaping Liu, Mehrtash Harandi
To enhance the performance of LDSs, in this paper, we address the challenging issue of performing sparse coding on the space of LDSs, where both data and dictionary atoms are LDSs.