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Synthetic Datasets for Neural Program Synthesis

, , , , , , и . (2019)cite arxiv:1912.12345Comment: ICLR 2019.

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Effective Data Augmentation With Diffusion Models., , , и . CoRR, (2023)Conservative Objective Models for Effective Offline Model-Based Optimization., , , и . ICML, том 139 из Proceedings of Machine Learning Research, стр. 10358-10368. PMLR, (2021)Synthetic Datasets for Neural Program Synthesis, , , , , , и . (2019)cite arxiv:1912.12345Comment: ICLR 2019.Design-Bench: Benchmarks for Data-Driven Offline Model-Based Optimization., , , и . ICML, том 162 из Proceedings of Machine Learning Research, стр. 21658-21676. PMLR, (2022)Discovering Non-monotonic Autoregressive Orderings with Variational Inference., , , , , , и . ICLR, OpenReview.net, (2021)Understanding Visual Concepts Across Models., , , и . CoRR, (2024)A Simple Approach for Visual Room Rearrangement: 3D Mapping and Semantic Search., , , , и . ICLR, OpenReview.net, (2023)Inferring the Optimal Policy using Markov Chain Monte Carlo., , , и . CoRR, (2019)Stylus: Automatic Adapter Selection for Diffusion Models., , , , , , , и . CoRR, (2024)AnyMorph: Learning Transferable Polices By Inferring Agent Morphology., , и . ICML, том 162 из Proceedings of Machine Learning Research, стр. 21677-21691. PMLR, (2022)