Shivam Saboo

@shivamsaboo17

Deep Learning Intern @ Intel Corporation | Ex Computer Vision Intern @ Technicolor R&I, France

India
Vrijeme pridruživanja: ožujak 2018.
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  1. proslijedio/la je Tweet
    4. velj

    "How to do machine learning efficiently". There's so much to love about this wonderful article.

    251 proslijeđeni tweet 1.160 korisnika označava da im se sviđa
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  2. proslijedio/la je Tweet
    31. sij

    An Opinionated Guide to ML Research: “To make breakthroughs with idea-driven research, you need to develop an exceptionally deep understanding of your subject, and a perspective that diverges from the rest of the community—some can do it, but it’s hard.”

    9 replies 238 proslijeđenih tweetova 858 korisnika označava da im se sviđa
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    29. sij

    Machine Learning Summer School 2020 is in Tuebingen, Germany! Please apply. Deadline: 11 Feb 2020.

    76 proslijeđenih tweetova 155 korisnika označava da im se sviđa
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  4. proslijedio/la je Tweet
    26. sij

    Teaching Deep Unsupervised Learning (2nd edition) at this semester. You can follow along here: Instructor Team: , , , Wilson Yan, Alex Li, YouTube, PDF, and Google Slides for ease of re-use

    Korisnici , i
    121 proslijeđeni tweet 413 korisnika označava da im se sviđa
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  5. proslijedio/la je Tweet
    28. sij

    Finally, Differentiable Physics is Here! ▶️Full video (ours): 📜Source paper:

    48 proslijeđenih tweetova 127 korisnika označava da im se sviđa
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    27. sij

    Kornia v0.2.0 is out ! We have introduced a new data augmentation module with strong GPU support, extended the set of color conversion algorithms, supporting GPU CI tests with v1.4.0, and much more. Happy coding !

    162 proslijeđena tweeta 518 korisnika označava da im se sviđa
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    27. sij

    TRADI: Tracking deep neural network weight distributions -- work with G. Franchi We’re proposing a cheap method for getting ensembles of networks from a single network training 1/

    29 proslijeđenih tweetova 129 korisnika označava da im se sviđa
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    21. sij

    Now it works. Let's spatially explore the 2D images! Thanks for tips, ! And Special Kudos to - 3D Ken Burns model is his great work! Here is what happens if you exaggerate this model. And it's amazing.

    7 replies 95 proslijeđenih tweetova 383 korisnika označavaju da im se sviđa
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    22. sij

    Excited to share PCGrad, a super simple & effective method for multi-task learning & multi-task RL: project conflicting gradients On Meta-World MT50, PCGrad can solve *2x* more tasks than prior methods w/ Tianhe Yu, S Kumar, Gupta, ,

    5 replies 101 proslijeđeni tweet 403 korisnika označavaju da im se sviđa
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    15. sij

    Visualizing the Impact of Feature Attribution Baselines -- A new Distill article by Pascal Sturmfels, Scott Lundberg, and Su-In Lee.

    55 proslijeđenih tweetova 183 korisnika označavaju da im se sviđa
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    9. sij

    We are organizing a workshop on Causal learning for Decision Making at along with , Jovana Mitrovic, , Stefan and . Consider submitting your work!

    6 replies 45 proslijeđenih tweetova 188 korisnika označava da im se sviđa
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    14. sij

    I often meet research scientists interested in open-sourcing their code/research and asking for advice. Here is a thread for you. First: why should you open-source models along with your paper? Because science is a virtuous circle of knowledge sharing not a zero-sum competition

    309 proslijeđenih tweetova 1.010 korisnika označava da im se sviđa
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    3. sij

    Seeking volunteers for the mentorship program at our workshop! Those with a climate change and/or machine learning background are encouraged to apply to mentor submissions from Jan 15-Feb 4. Apply to be a mentor (or mentee) at:

    1 reply 13 proslijeđenih tweetova 31 korisnik označava da mu se sviđa
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  14. proslijedio/la je Tweet
    2. sij

    Maximizing acquisition functions in Bayesian optimization is hard. However, they have some nice properties (e.g., reparametrizable, submodular), which can be useful (also in the parallel setting) as discussed by James Wilson

    1 reply 36 proslijeđenih tweetova 117 korisnika označava da im se sviđa
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    1. sij

    ***What were the most interesting, scientifically insightful, and coherent papers that you read in 2019??*** Rules: 1) No restriction on methodology or aim (theoretical, experimental, & applications papers welcome). 2) Do not post your own papers.

    37 replies 99 proslijeđenih tweetova 510 korisnika označava da im se sviđa
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  16. proslijedio/la je Tweet
    2. sij

    Perhaps 2019 was the yr neural architectures died. Architecture papers still form plurality of submissions (bc its easy) but most *interesting* papers are agnostic. 2012-2018 = "how do we learn fn approx. for given p(x,y)?" 2019-???? = "we have good fn approx., now what?"

    9 replies 26 proslijeđenih tweetova 313 korisnika označava da im se sviđa
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  17. proslijedio/la je Tweet
    31. pro 2019.

    What companies look for when hiring 1960: People who know many things 1990: People who are good at learning new things 2020: People who are good at learning how to learn new things

    27 replies 148 proslijeđenih tweetova 959 korisnika označava da im se sviđa
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    30. pro 2019.

    This is an important story to read for anyone in DL academia

    9 replies 75 proslijeđenih tweetova 381 korisnik označava da mu se sviđa
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    28. pro 2019.

    It would help the discussion if everyone first 1. reads a causal inference book, eg , 2. watches a deep learning course emphasising modularity, compositionality and automatic differentiation, 3. implements the CI book examples in eg

    I am retweeting this reply, for it crystallizes my position in the latest conversation on the relationships between DL (deep learning) and CI (causal inference) with , , , and significant others.
    80 proslijeđenih tweetova 364 korisnika označavaju da im se sviđa
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  20. proslijedio/la je Tweet
    27. pro 2019.

    The 1997 LSTM paper by Hochreiter & Schmidhuber has become the most cited deep learning research paper of the 20th century

    152 proslijeđena tweeta 577 korisnika označava da im se sviđa
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