Orlando Dohring
@orl_LondonResearch in machine learning and statistical pattern recognition.
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An Adaptive Approach for Anomaly Detector Selection and Fine-Tuning in Time Series: arxiv.org/abs/1907.07843
Applying machine learning in capital markets: Pricing, valuation adjustments, and market risk: mckinsey.com/business-funct…
Quarter-century anniversary: 25 years ago we received a message from N(eur)IPS 1995 informing us that our submission on LSTM got rejected. (Don’t worry about rejections. They mean little.) #NeurIPS2020 people.idsia.ch/~juergen/deep-…
Crypto regulation in the UK: Assessing opportunity through the looking glass dlvr.it/RcyKtt
We overlapped at Bell Labs and he was a model for working on only and whatever was interesting and fun. nytimes.com/2020/07/23/sci…
Academic members of UCL’s AI Centre have been successful in achieving a number of accepted papers, talks and workshops at @icmlconf 2020, the thirty-seventh International Conference on Machine Learning. Read more: ucl.ac.uk/ai-centre/news… #UCL #AI #icml2020
How can robots learn in changing, open-world environments? We study: Deep Reinforcement Learning amidst Lifelong Non-Stationarity arxiv.org/abs/2006.10701 with Annie Xie, @jmes_harrison @StanfordAILab (1/5)
Interesting paper that looks at unsupervised machine translation between different programming languages (like a trancompiler) but maintains elements of readability and language specific conventions. Could be useful for working with legacy COBOL systems! arxiv.org/abs/2006.03511
Unsupervised Translation of Programming Languages. Feed a model with Python, C++, and Java source code from GitHub, and it automatically learns to translate between the 3 languages in a fully unsupervised way. arxiv.org/pdf/2006.03511… with @MaLachaux @b_roziere @LowikChanussot
In this lecture, @ThoreG explains our machine learning based approach towards AI. He shows how deep learning and RL can be combined to build intelligent systems - including AlphaGo, AlphaStar & more. Watch it in full here: bit.ly/2TXNOTs (@ai_ucl) #AtHomeWithAI
Super excited to announce that “Dive Into Deep Learning” now officially supports PyTorch! d2l.ai
Dive into Deep Learning now supports @PyTorch The first 8 chapters are ready with more on their way. Thanks to DSG IIT Roorkee @dsg_iitr, particularly @gollum_here who adapted the code into PyTorch. More at D2L.ai. @mli65 @smolix @zacharylipton @astonzhangAZ
The Remdesivir placebo-controlled randomized trial data. We've eagerly awaited the data; now published @NEJM nejm.org/doi/pdf/10.105… Significant benefit for 27% ⬇️time to recovery, across all subgroups except those on a ventilator/ECMO, death reduced 30% (95% CI 0.47, 1.04; NS)
El-Erian on the Long-Term Effects of the Crisis: investopedia.com/mohamed-el-eri…
Neural forecasting: Introduction and Literature Overview [66pp] By Amazon Research @LoVVgE @canerturkmen @lostella Concise Deep Learning introduction through the prism of Forecasting. arxiv.org/abs/2004.10240
UK Mathematics Trust - Past downloadable Olympiad Papers free for download during COVID-19 time: ukmt.org.uk/shop?body_valu…
Potential COVID-2019 3C-like Protease Inhibitors Designed Using Generative Deep Learning Approaches: chemrxiv.org/articles/Poten…
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