jiayaozhang

3 ms·

1. 1.▲
   Rock: Causal Inference Principles for Reasoning about Commonsense Causality(arxiv.org)

   7 points by jiayaozhang 4y ago|1 comments
2. 2.▲
   Some Reflections on Drawing Causal Inference Using Textual Data(arxiv.org)

   11 points by jiayaozhang 5y ago|0 comments
3. 3.▲
   by jiayaozhang 5y ago

   Thanks for the heads-up! Yes, we use vector graphics in pdf formats for all figures (outputted from matploblib). I overlooked the size of the arXiv version but my local complication is around 14.5MB (pdflatex under TexLive 2020). I will che
4. 4.▲
   by jiayaozhang 5y ago

   Thanks for sharing the interesting IRM paper! Will read and be back for discussion hopefully soon.
5. 5.▲
   by jiayaozhang 5y ago

   > I thought the main selling point of deep learning that it finds non-linear connections in the data. Agreed. Yet there are unknown feature spaces in which the deep nets separate the data linearly; the mapping learnt by the deep nets fro
6. 6.▲
   by jiayaozhang 5y ago

   > does it have direct application for training nets faster? That's a great question! Unfortunately not yet -- though we believe further studies may bring us there finally. We found (at least for simple classification tasks) the feat
7. 7.▲
   by jiayaozhang 5y ago

   Hello HackerNews! Author here :) TL;DR: We devise a linear SDE/ODE model to imitate per-class feature (thinking logits) dynamics of neural nets training based on local elasticity (LE) [1]. We found the emergence of LE implies linear s
8. 8.▲
   by jiayaozhang 5y ago

   Most websites I visited then denied my visit; finally I settled by using an ad blocker to block their prompts.
9. 9.▲
   Imitating Deep Learning Dynamics via Stochastic Differential Equations(arxiv.org)

   122 points by jiayaozhang 5y ago|21 comments