📚 ICLR’24 has finally opened all submissions on OpenReview - we will have the weekend reading! Apart from the papers already available on arxiv and/or rejected from past conferences, one could find new, fresh, and anonymous hidden gems (sometimes even with the implementation in the supplementary). See the first batch of new Graph & Geometric DL papers that haven’t yet appeared on Twitter in the previous post.
🦦 Flow Matching papers continue to conquer the generative world - this week MIT and Microsoft Research released two new works: FlowSite from Hannes Stärk et al on protein-ligand docking and FrameFlow from Jason Yim et al on protein backbone generation. Both models significantly improve over the previous generation of diffusion-based approaches.
⌨️ PyG 2.4 was released this week. The newest version brings the support of
torch.compile() to GNNs - compiled GNNs yield up to 300% speed boosts. Previously, compilation of GNNs wouldn’t be that useful on inductive tasks when the graph or a batch of graphs have different shapes, but PyTorch 2.1 makes dynamic shaping more friendly. JAX aficionados might look at this with a humble smile, but guys, the torch community is catching up.🪐 Polymathic is a new initiative to bring foundation models into the world of complex scientific problems. The announcement release features models for numbers encoding (so LLMs can better work with floats), models for learning physics and dynamical systems, and AstroCLIP for matching galaxy spectra with their images.
Weekend reading:
See the previous post with ICLR’24 submissions