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FIGARO: Controllable Music Generation using Learned and Expert Features

, , , and . The Eleventh International Conference on Learning Representations, (February 2023)

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FIGARO: Controllable Music Generation using Learned and Expert Features, , , and . The Eleventh International Conference on Learning Representations, (February 2023)On the effectiveness of Randomized Signatures as Reservoir for Learning Rough Dynamics., , , , , and . IJCNN, page 1-8. IEEE, (2023)An SDE for Modeling SAM: Theory and Insights., , , , , and . ICML, volume 202 of Proceedings of Machine Learning Research, page 25209-25253. PMLR, (2023)Signal Propagation in Transformers: Theoretical Perspectives and the Role of Rank Collapse., , , , , and . NeurIPS, (2022)Neural Symbolic Regression that scales., , , , and . ICML, volume 139 of Proceedings of Machine Learning Research, page 936-945. PMLR, (2021)Controllable Neural Symbolic Regression., , and . ICML, volume 202 of Proceedings of Machine Learning Research, page 2063-2077. PMLR, (2023)Harnessing Synthetic Datasets: The Role of Shape Bias in Deep Neural Network Generalization., , , and . CoRR, (2023)Dynamic Context Pruning for Efficient and Interpretable Autoregressive Transformers., , , , , and . CoRR, (2023)Self-supervised pre-training on industrial time-series., and . SDS, page 56-57. IEEE, (2021)Transformers beyond natural language: a theoretical and empirical investigation.. ETH Zurich, Zürich, Switzerland, (2023)base-search.net (ftethz:oai:www.research-collection.ethz.ch:20.500.11850/644515).