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ORCIDDan Shiebler
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Journal Articles
- 2021
[j1]Dan Shiebler:
Categorical Stochastic Processes and Likelihood. Compositionality 3: 1 (2021)
Conference and Workshop Papers
- 2021
- [c4]Dan Shiebler:
Generalized Optimization: A First Step Towards Category Theoretic Learning Theory. ICO 2021: 525-535 - [c3]Dan Shiebler:
Functorial Manifold Learning and Overlapping Clustering. ACT 2021: 1-13 - 2020
- [c2]Benjamin Paul Chamberlain, Emanuele Rossi, Dan Shiebler, Suvash Sedhain, Michael M. Bronstein:
Tuning Word2vec for Large Scale Recommendation Systems. RecSys 2020: 732-737 - 2019
- [c1]Drew Linsley, Dan Shiebler, Sven Eberhardt, Thomas Serre:
Learning what and where to attend. ICLR (Poster) 2019
Parts in Books or Collections
- 2020
- [p1]Shane O'Sullivan
, Fleur Jeanquartier, Claire Jean-Quartier, Andreas Holzinger, Dan Shiebler, Pradip Moon, Claudio Angione:
Developments in AI and Machine Learning for Neuroimaging. AI and ML for Digital Pathology 2020: 307-320
Informal and Other Publications
- 2022
- [i10]Dan Shiebler:
Kan Extensions in Data Science and Machine Learning. CoRR abs/2203.09018 (2022) - 2021
- [i9]Dan Shiebler:
Flattening Multiparameter Hierarchical Clustering Functors. CoRR abs/2104.14734 (2021) - [i8]Alim Virani, Jay Baxter, Dan Shiebler, Philip Gautier, Shivam Verma, Yan Xia, Apoorv Sharma, Sumit Binnani, Linlin Chen, Chenguang Yu:
Lessons Learned Addressing Dataset Bias in Model-Based Candidate Generation at Twitter. CoRR abs/2105.09293 (2021) - [i7]Dan Shiebler, Bruno Gavranovic, Paul W. Wilson:
Category Theory in Machine Learning. CoRR abs/2106.07032 (2021) - [i6]Dan Shiebler:
Generalized Optimization: A First Step Towards Category Theoretic Learning Theory. CoRR abs/2109.10262 (2021) - 2020
- [i5]Dan Shiebler, Alexis Toumi, Mehrnoosh Sadrzadeh:
Incremental Monoidal Grammars. CoRR abs/2001.02296 (2020) - [i4]Dan Shiebler:
Categorical Stochastic Processes and Likelihood. CoRR abs/2005.04735 (2020) - [i3]Benjamin Paul Chamberlain, Emanuele Rossi, Dan Shiebler, Suvash Sedhain, Michael M. Bronstein:
Tuning Word2vec for Large Scale Recommendation Systems. CoRR abs/2009.12192 (2020) - 2018
- [i2]Dan Shiebler:
A Correlation Maximization Approach for Cross Domain Co-Embeddings. CoRR abs/1809.03497 (2018) - [i1]Dan Shiebler, Luca Belli, Jay Baxter, Hanchen Xiong, Abhishek Tayal:
Fighting Redundancy and Model Decay with Embeddings. CoRR abs/1809.07703 (2018)
Coauthor Index
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