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Tristan
rice_fry
We recently got some insight into how Tesla is going to replace radar in the recent firmware updates + some nifty ML model techniques Thread From the binaries we can
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_vxhl_
MohariVishal
#1. Recurrent Neural Networks: Understanding Long Short Term Memory ( LSTM ) Networks { A self-study thread } #WhoKnowsHowManyDaysOfThreads Before jumping into the topic's core (meat and potatoes), let us
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Jelle Zuidema
wzuidema
My PhD student @samiraabnar has written a series of blogs about her two latest papers. The first is ‘bertology’: figuring out how the Transformer arrives at its predictions by tracking
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Objectif Data Science - avec Vincent
ObjectifDataSci
1. Helloles réseaux #RNN de type #LSTM et #GRU sont des réseaux qui sont généralement mal comprisJe vais essayer dans ce thread de les expliquer clairementon va commencer par voir
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Priyesh Patel
PriyeshPatelUK
Things can get a little confusing when you first dive into learning about deep neural networks. It helps to understand some basic ideas and rules of thumb. The first is
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Myles McNulty
MylesMcNulty
More great news from #AVCT: it has developed a research use only ('RUO') ELISA test for #COVID19.There are also a number of very helpful snippets and implications in the RNS
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Tim Dettmers
Tim_Dettmers
How can you successfully train transformers on small datasets like PTB and WikiText-2? Are LSTMs better on small datasets? I ran 339 experiments worth 568 GPU hours and came up
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Prakash Kagitha @ICLR'20
prakashkagitha
Our work 'Systematic generalization emerges in Seq2Seq models with variability in data' published at #ICLR2020 workshop Bridging Cognitive Science and AI.We show that LSTM+attn model can exhibit sys.gen. and analyze
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Quant@LSTM
BeingHorizontal
Thread for beginners; How to learn machine learning. Let’s start with something really simple and useful not just for Machine Learning. Start with a Python library called pandas. It’s a
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sistemsko irelevanten
tadejtadej
So, the time has come to find somewhere to work as again. Some sort of Data Scientist / ML Engineer / Applied Scientist role. I have >10 years of experience
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Alex Rives
alexrives
1/9 Today we’re excited to release Transformer models pre-trained on evolutionary-scale protein sequence data along with a major update to our preprint from last year:Paper: https://www.biorxiv.org/content/10.1101/622803v3Models: https://
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Prakash Kagitha @ICLR'20
prakashkagitha
#ICLR2020 is here and I am excited about our paper at #BAICS2020 so, I wrote an introduction to systematic generalization (the thing our work explores) and discussed 4 papers from
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Stat Arb
quant_arb
Back to the quant topics:Microstructural fair value!Let's dive into it:1/n The usual approach is to take the midprice which is just the average between the best bid and ask. This
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Petar Veličković
PetarV_93
The crowd has spoken! A thread with early-stage machine learning research advice follows below. Important disclaimer before proceeding: these are my personal views only, and likely strongly biased by
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Bharath Ramsundar
rbhar90
Going to tweet out a few ICLR submissions that look interesting based on their abstracts:https://openreview.net/forum?id=8mVSD0ETOXl Here's a neat theoretical paper on the capability of graph networks on the graph coloring
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Stat Arb
quant_arb
Non-prediction/main-model alpha (this is HUGE), let's talk about it!Topics:-Regime Shift (an extension of risk mgmt)-Position Sizing-Trade Specific Risk Mgmt-Whole Algo Risk Mgmt-Execution Starting with the risk side of things it
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