Rajeev Ranjan Dwivedi @RajeevRanjanDw3
Life is in data science and research. Everything else is overrated. Doctoral Researcher at @iiserbhopal rajeev-dw9.github.io India Joined January 2021-
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I am thrilled to share that our paper "Quantifying uncertainty in Neural Networks through residuals" has been accepted as a short paper in CIKM 2024. Authors: D. Udbhav, T. Rini, Rajeev and Vinod K. Kurmi. #CIKM2024 #ai #ml #research
Damn it.. I was supposed to use my week off to relax but I accidentally made a video about why neural nets love the softmax. I'm not relaxed at all. youtu.be/p-6wUOXaVqs
My controversial opinion: Bayes is guaranteed to overfit, for any model, any prior, and any data point yulingyao.com/blog/2023/over…
IISER Bhopal bags 8th position in India for research output according to nature index. natureindex.com/institution-ou…
@Wilyzein I break up everything into 12 to 16 weeks cycles, and I match my work to my physical training schedule. I’ve been doing this for 25 years. So far, so good!
Another panel I like, on Gaussian Processes. It says GP hypers give a (prior) distribution over functions. When they're optimized, we pick the distribution that agrees most with the data. That agreement is related to how much red👇 Also, it's a differentiable optimization 🤯
1/5 📣We are thrilled to announce that PyMC 4.0 is out! Try it out with: >conda install -c conda-forge pymc #PyMCv4 Release announcement: pymc.io/blog/v4_announ…
New book on the reading list: Data Science in Context: Foundations, Challenges, Opportunities By Alfred Spector, Peter Norvig, Chris Wiggins, Jeannette M. Wing Prerelease below datascienceincontext.com/manuscript/
I’ve been using #AnnotatedEquations in my recent papers. I think it really adds to the readability and understanding of the math. Here are some examples. It uses #tikz in #latex. Let me know if you like it. Happy for any feedback. [GitHub link: next tweet] #AcademicChatter +
Researchers in speech recognition, computer vision, and natural language processing in the 2000s were obsessed with accurate representations of uncertainty. 1/N
Short writeup on my experience with PyScript. For programming enthusiasts definitely something to pay attention to. For Python devs certainly something to start supporting ravinkumar.com/PyScriptFirstI…
The "Don't Repeat Yourself" principle for programming is overrated. A ton of code gets used just once.. right after it was written. So optimizing for wishful re-use can be a waste of time. I'd say if you're not writing tests for your code, no need to generalize it.
You can’t find a more comprehensive and consistent review of modern machine learning than with these two books (here is the 2nd). A top notch education is available here - you just need to be willing to read.. a lot.
You can’t find a more comprehensive and consistent review of modern machine learning than with these two books (here is the 2nd). A top notch education is available here - you just need to be willing to read.. a lot.
If you’re 20-30 and your main circle isn’t discussing: - Buying the dip - Fed rate hikes - Crypto bear market Then it’s time to find a new circle
Are you familiar with Factor Analysis and Probabilistic PCA? If not, I can change that in ~18 minutes. youtu.be/lJ0cXPoEozg
Here’s an easy way to understand the relation of soft arg max and arg max
Here’s an easy way to understand the relation of soft arg max and arg max
Studying causal inference makes you realize how hard *really* knowing *anything* is.
Changing my parroted definition on the p value to be The P value is the probability that the chosen test statistic would have been at least as large as its observed value if every model assumption were correct, including the test hypothesis
If a language model is trained on Twitter to learn humor, it’s going to think puns are funny 🤦♂️
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