Today is a great day! Saad will be defending his thesis. The last student of the @solar2chem team, presents an amazing research trip and our first in collaboration with Ricard Garcia-Valls @universitatURV. With one of the first uses of MLIPs for transport in membranes.
I revisit the classical HER beyond low-coverage Sabatier
constraints and found a alternative HER pathway and its theoretical descriptors. Metal centers pre-concentrate H and form di-hydrogen complexes at monolayer coverage, explaining the high experimental activity.
Excellent news coming... trying different synthesis routes is always fun. Thanks to Menny for the leadership and Saad for smoothly running our simulations!
Is this one of the most famous equations in physics?
The Schrödinger equation is a cornerstone of quantum physics - the analogue of Newton's second law for quantum mechanics. Its derivation led to Schrödinger, born on this day in 1887, receiving the 1933 Nobel Prize in Physics.
So happy that this collaboration with @at_bgu Menny's group went so nicely.
We love cascades! Enjoy the Solstice and thanks Saad for your great computational work!
https://t.co/gmiemuuMR3
The GPT Surprise😮! We ran one of the first controlled experiments on the impacts of ChatGPT for learning. We ran it in a massive #python course @StanfordEng. Many classes have deployed AI tutors, but very few have studied the causal effects on a #education. Can you guess the impact?... 🔬🎓
1/ Machine learning force fields are hot right now 🔥: models are getting bigger + being trained on more data. But how do we balance size, speed, and specificity? We introduce a method for doing model distillation on large-scale MLFFs into fast, specialized MLFFs!
Stuck at my fraud detection project. Below is the best result using XGBoost and after tuning class weights on a highly imbalanced dataset (600:1). Selective sampling of any kind or F.Eng produces inferior results. Targetting high recall. Any suggestions?
I just posted a new video, originally made as part of a new exhibit at the Computer History Museum on the history of chatbots.
My hope is that it offers a lighter-weight, but still substantive, intro to Large Language Models, complementing the more technical breakdown of the underlying architecture that other videos of the channel cover.
https://t.co/xZBIq3S9QM
@svpino New to ML and doing baby projects like price prediction and fraud detection. Should I bother deploying them? I feel like I am learning but seeing the current rate of progress, I thinm I should be doing RAG or something related to LLMs.
Happy Tau Day! As something a little different, here’s a clip from a bit I did at @standupmaths's “Evening of Unnecessary Detail” a few years ago.
Full video here: https://t.co/BNlCsRaCQY
@Fidias0 1- Create "Productive" jobs. Regulation and admin jobs must decrease. 2- ⬆️ R&D budget +add startup investments. Fund innovative risk-takers and local manufacturing and technology.
I am confused. After outlier removal, manual feature eng and insistence on using simple models (LinReg, Ridge), I got the following results for my house price prediction. Should I shift to DL models for better results or explore feature engineering further? 🤔 #newbie
Laying my ML foundation by completing Mathematics for Machine Learning and Data Science by https://t.co/lT4yJ2rska. Learned and coded PCA, Gradient Descent and a complete Neural Network from scratch. https://t.co/VnGU3LCiSc #Coursera
@MushtaqBilalPhD What does an academic family even mean? A players nuture A players. One can argue about the scale of funding in such labs but that doesn’t promise a nobel.
We all memorized that the derivative of x² is 2x, but do we actually know why? Let’s actually see it visually—I promise it’s more satisfying than just memorizing!
🧵