bookmarks (hide)368
- Streamlit is an open-source app framework for Machine Learning and Data Science teams. Create beautiful web apps in minutes.
- GAN-based Mel-Spectrogram Inversion Network for Text-to-Speech Synthesis - GitHub - descriptinc/melgan-neurips: GAN-based Mel-Spectrogram Inversion Network for Text-to-Speech Synthesis
- StyleGAN - Official TensorFlow Implementation. Contribute to NVlabs/stylegan development by creating an account on GitHub.
- starter from "How to Train a GAN?" at NIPS2016. Contribute to soumith/ganhacks development by creating an account on GitHub.
- Interactive deep learning book with multi-framework code, math, and discussions. Adopted at 400 universities from 60 countries including Stanford, MIT, Harvard, and Cambridge. - GitHub - d2l-ai/d2l-en: Interactive deep learning book with multi-framework code, math, and discussions. Adopted at 400 universities from 60 countries including Stanford, MIT, Harvard, and Cambridge.
- VegaFusion provides serverside acceleration of the Vega visualization grammar
- Turns even the largest data into images, accurately.
- A library for efficient similarity search and clustering of dense vectors. - GitHub - facebookresearch/faiss: A library for efficient similarity search and clustering of dense vectors.
- tomotopy is a Python extension of tomoto (Topic Modeling Tool) which is a Gibbs-sampling based topic model library written in C++. It utilizes a vectorization of modern CPUs for maximizing speed. The current version of tomoto supports several major topic models including
- Force-directed layout algorithms for Python
- Building chord diagrams in d3.js: simple and customized examples with reproducible code.
- Using d3.js to create a very basic network graph
- Learn how to draw graphs using LaTeX.
- In this 3-part blog series we present a unifying perspective on pre-trained word embeddings under a general framework of matrix factorization. The most popular word embedding model, Word2vec, has…
publications (hide)217
- Proceedings of the 18th Annual International Conference on Mobile Computing and Networking , page 269--280. New York, NY, USA, ACM, (2012)
- IEEE Transactions on Parallel and Distributed Systems 24 (4): 839-848 (2013)
- Program 14 (3): 130-137 (1980)
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- Princeton University Press, (1961)
- International Journal on Digital Libraries 17 (4): 305--338 (2016)
- (2021)cite arxiv:2109.11343.
- (2021)cite arxiv:2106.09789Comment: 18 pages.
- Proceedings of the 29th International Coference on International Conference on Machine Learning , page 9–16. Madison, WI, USA, Omnipress, (2012)
- Nature Machine Intelligence 1 (5): 206--215 (2019)
- DSAA , page 165-174. IEEE, (2017)
- Expert Syst. Appl. 42 (13): 5645-5657 (2015)
- Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining , page 2105–2114. New York, NY, USA, Association for Computing Machinery, (2016)
- KDD , page 490-499. ACM, (2007)
- J. Assoc. Inf. Sci. Technol. 61 (9): 1871-1887 (2010)
- J. Assoc. Inf. Sci. Technol. 68 (1): 214-233 (2017)
- (2017)cite arxiv:1702.08608.
- Journal of Open Source Software 3 (32): 1057 (2018)
- CoRR (2019)
