PhyloGFN: Phylogenetic inference with generative flow networks

arXiv:2310.08774 · q-bio.PE, cs.LG, stat.ML · Submitted 2023-10-12 · Read on arXiv

q-bio.PE, cs.LG, stat.ML

Submitted: 2023-10-12

Updated: 2026-08-31

Code: https://github.com/zmy1116/phylogfn

Terminology

• Parsimony — 62× in this paper · explained in 2 episodes
• Benchmark — 15× in this paper · explained in 2 episodes
• Transformer — 11× in this paper · explained in 2 episodes
• Bayesian Inference — 6× in this paper · explained in 5 episodes
• Core — 5× in this paper · explained in 2 episodes
• Reward Function — 5× in this paper · explained in 2 episodes
• Embeddings — 4× in this paper · explained in 2 episodes
• Action Space — 3× in this paper · explained in 1 episode
• Computational Biology — 3× in this paper · explained in 2 episodes
• International Conference on Learning Representations — 3× in this paper
• Neural Information Processing Systems — 3× in this paper
• Quantization — 3× in this paper · explained in 12 episodes
• Ablation — 2× in this paper · explained in 1 episode
• Generative Model — 2× in this paper · explained in 2 episodes
• Generative Models — 2× in this paper · explained in 2 episodes
• International Conference on Machine Learning — 2× in this paper
• Ablation study — 1× in this paper · explained in 1 episode
• Adaptation — 1× in this paper · explained in 1 episode
• Alignment — 1× in this paper · explained in 1 episode
• Calibration — 1× in this paper · explained in 7 episodes
• Consistency — 1× in this paper · explained in 3 episodes
• Credit assignment — 1× in this paper · explained in 3 episodes
• Downstream Tasks — 1× in this paper · explained in 2 episodes
• Fidelity — 1× in this paper · explained in 2 episodes
• Generative Modeling — 1× in this paper · explained in 3 episodes
• Markov Decision Process (MDP) — 1× in this paper · explained in 11 episodes
• Pruning — 1× in this paper · explained in 4 episodes
• Reinforcement Learning — 1× in this paper · explained in 4 episodes
• Transformer Architecture — 1× in this paper · explained in 2 episodes
• Uncertainty in Artificial Intelligence — 1× in this paper

Sources

• Joint Bayesian Inference of Graphical Structure and Parameters with a Single Generative Flow Network
• GeoPhy: Differentiable Phylogenetic Inference via Geometric Gradients of Tree Topologies
• Learnable Topological Features for Phylogenetic Inference via Graph Neural Networks
• Let the Flows Tell: Solving Graph Combinatorial Optimization Problems with GFlowNets

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