Aleksander Molak
where else to find them
website:https://bit.ly/aleksander-molak
github:AlxndrMlk
bluesky:alxndrmlk.bsky.social
linkedin:aleksandermolak
youtube:@CausalPython
what they talk about
where they keep going back
no series more than once — all 4 in the filters
on a stage with
- Uri Itaionce
who talks about the same things
- Vincent D Warmerdam22 talks
- Daniel Whitenack5 talks
- Kyryl Truskovskyi2 talks
- Anima Anandkumar7 talks
- Vaibhav Singh8 talks
- Benjamin Batorsky3 talks
| title | conference | date |
|---|---|---|
| A Practical Guide to Causality in Python (For The Perplexed) | PyData NYC 2023 | 2023-11-01 |
Practical steps and code in Python: builds causal graphs, encodes assumptions, uses front-door/back-door/do-calculus to translate queries into estimable… | ||
| Flexibility General Average for ML | PyData Tel Aviv 2022 | 2022-12-13 |
Presents a continuous, differentiable operator called Generalized Average (GA) that interpolates min, max, arithmetic, geometric and harmonic means; shows two… | ||
| Applying contrastive learning to fight anisotropy in language models | PyData Global 2022 | 2022-12-01 |
Claim: applying SimCSE (contrastive objective) with dropout augmentation turns cone-like BERT/Roberta embeddings into a more spherical, isotropic distribution… | ||
| Practical graph neural networks in Python with TensorFlow and Spektral | PyCon DE & PyData Berlin 2022 | 2022-04-11 |
Live code shows GNNs implemented with TensorFlow and Spektral, using Colab/GPU, concrete layers GCN and GAT, and dataset plumbing (single vs disjoint loaders)… | ||
| nothing matches | ||