Papers
Deep Bidirectional Language-Knowledge Graph Pretraining
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Michihiro Yasunaga, Antoine Bosselut, Hongyu Ren, Xikun Zhang, Christopher D Manning, Percy Liang, Jure Leskovec
PDF | ICLR schedule |
SlotDiffusion: Unsupervised Object-Centric Learning with Diffusion Models
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LAMBADA: Backward Chaining for Automated Reasoning in Natural Language
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Deep Generative Symbolic Regression with Monte-Carlo-Tree-Search
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A-NeSI: A Scalable Approximate Method for Probabilistic Neurosymbolic Inference
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Emile van Krieken, Thiviyan Thanapalasingam, Jakub Mikolaj Tomczak, Frank van Harmelen, Annette Ten Teije
PDF | ICLR schedule |
VAEL: Bridging Variational Autoencoders and Probabilistic Logic Programming
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Slot-VAE: Slot Attention enables Object-Centric Scene Generation
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Learning Symbolic Representations Through Joint GEnerative and DIscriminative Training
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Symbolic Disentangled Representations in Hyperdimensional Latent Space
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Generating Temporal Logical Formulas with Transformer GANs
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Using Domain Knowledge to Guide Dialog Structure Induction via Neural Probabilistic Soft Logic
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Connor Pryor, Quan Yuan, Jeremiah Zhe Liu, Seyed Mehran Kazemi, Deepak Ramachandran, Tania Bedrax-Weiss, Lise Getoor
PDF | ICLR schedule |
Discovering Graph Generation Algorithms
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Guaranteed Conformance of Neurosymbolic Dynamics Models to Natural Constraints
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Grounded physical language understanding with probabilistic programs and simulated worlds
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Open-Ended Dreamer: An Unsupervised Diversity-Oriented Neurosymbolic Learner
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