apoorvalal.github.io
(passively) maintains @paperposterbot.bsky.social
my config morphed into a whole spongebob-themed thing
apoorvalal.github.io/lalgorithms/...
my config morphed into a whole spongebob-themed thing
apoorvalal.github.io/lalgorithms/...
New linklog: new long term paper w Imbens and Hull, new job, RL<> Causal Rosetta Stone, demand elasticity simulator, and some nice metrics papers
New linklog: new long term paper w Imbens and Hull, new job, RL<> Causal Rosetta Stone, demand elasticity simulator, and some nice metrics papers
1) trimming is bulletproof since it's just ffmpeg
2) stemming is reasonable
3) midi is hit-or-miss
4) tabs are underwhelming
github.com/apoorvalal/m...
1) trimming is bulletproof since it's just ffmpeg
2) stemming is reasonable
3) midi is hit-or-miss
4) tabs are underwhelming
github.com/apoorvalal/m...
what does this look like for other networks? cc @jugander.bsky.social
code: gist.github.com/apoorvalal/6...
what does this look like for other networks? cc @jugander.bsky.social
1. minishoot' adventures
wildly ambitious 2D zelda-like with a spaceship. also wins award for the most unnecessary apostraphy of all time.
1. minishoot' adventures
wildly ambitious 2D zelda-like with a spaceship. also wins award for the most unnecessary apostraphy of all time.
lalten.org/daylight
sanity checks:
- reproduce solstices as D'(t) crossing y=0
- equator has flat D(t), D'(t)
[cc @dggoldst.bsky.social who frequently posts about D''(t) ]
lalten.org/daylight
sanity checks:
- reproduce solstices as D'(t) crossing y=0
- equator has flat D(t), D'(t)
[cc @dggoldst.bsky.social who frequently posts about D''(t) ]
1. scrappy theory
2. killer empirical application (Angrist/Krueger for IV, Card/Krueger for DID, Lee for RD etc)
3. Deep, general theory
4. Review papers
5. Bad empirical applications
6. Empirical reviews
Proximal has skipped 2 entirely. Is this typical for epi methods?
Demystifying Proximal Causal Inference (Ringlein, Nguyen, Zandi et al) Proximal causal inference (PCI) has emerged as a promising framework for identifying and estimating causal effects in the presence of unobserved confounders. While many traditional causal inference methods rely on the
1. scrappy theory
2. killer empirical application (Angrist/Krueger for IV, Card/Krueger for DID, Lee for RD etc)
3. Deep, general theory
4. Review papers
5. Bad empirical applications
6. Empirical reviews
Proximal has skipped 2 entirely. Is this typical for epi methods?
chromewebstore.google.com/detail/math-...
chromewebstore.google.com/detail/math-...
Instead, just type in the latex expression and get back unicode that you can ctrl/cmd+F easily
github.com/apoorvalal/m...
Instead, just type in the latex expression and get back unicode that you can ctrl/cmd+F easily
github.com/apoorvalal/m...
(Tolerable semi-public social media, for all its faults, was nice while it lasted. Made parasocial and IRL friends, learned a lot. Now everyone's back on whatsapp and discord boards)
(Tolerable semi-public social media, for all its faults, was nice while it lasted. Made parasocial and IRL friends, learned a lot. Now everyone's back on whatsapp and discord boards)
dosaygo-studio.github.io/hn-front-pag...
dosaygo-studio.github.io/hn-front-pag...
read/tinker: pricingexperiments.streamlit.app
read/tinker: pricingexperiments.streamlit.app
missing.csail.mit.edu/2026/
missing.csail.mit.edu/2026/