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Found 10 papers, 7 papers with code
BioPlanner: Automatic Evaluation of LLMs on Protocol Planning in Biology
Here we present an automatic evaluation framework for the task of planning experimental protocols, and we introduce BioProt: a dataset of biology protocols with corresponding pseudocode representations.
PlanE: Representation Learning over Planar Graphs
Graph neural networks are prominent models for representation learning over graphs, where the idea is to iteratively compute representations of nodes of an input graph through a series of transformations in such a way that the learned graph function is isomorphism invariant on graphs, which makes the learned representations graph invariants.
Shortest Path Networks for Graph Property Prediction
Most graph neural network models rely on a particular message passing paradigm, where the idea is to iteratively propagate node representations of a graph to each node in the direct neighborhood.
Temporal Knowledge Graph Completion using Box Embeddings
Temporal knowledge graph completion (TKGC) is an extension of this task to temporal knowledge graphs, where each fact is additionally associated with a time stamp.
Knowledge Graph Embedding
Temporal Knowledge Graph Completion
Node Classification Meets Link Prediction on Knowledge Graphs
Node classification and link prediction are widely studied in graph representation learning.
The Surprising Power of Graph Neural Networks with Random Node Initialization
In this work, we analyze the expressive power of GNNs with RNI, and prove that these models are universal, a first such result for GNNs not relying on computationally demanding higher-order properties.
BoxE: A Box Embedding Model for Knowledge Base Completion
Knowledge base completion (KBC) aims to automatically infer missing facts by exploiting information already present in a knowledge base (KB).
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On the Approximability of Weighted Model Integration on DNF Structures
Weighted model counting (WMC) consists of computing the weighted sum of all satisfying assignments of a propositional formula.
CounterExample Guided Neural Synthesis
Program synthesis is the generation of a program from a specification.
Learning to Reason: Leveraging Neural Networks for Approximate DNF Counting
Weighted model counting (WMC) has emerged as a prevalent approach for probabilistic inference.
