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Delta: Publications

Publications

Publications resulting from research conducted using Delta appear here. Check back to see how the list of exciting discoveries made using Delta grows.

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Zhou, Y., Cersonsky, R. K. & Glotzer, S. C. A route to hierarchical assembly of colloidal diamond. Soft Matter 18, 304–311 (2022).
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Lui, H. F. S., Wolf, W. R., Ricciardi, T. R. & Gaitonde, D. V. Mach number effects on shock-boundary layer interactions over curved surfaces of supersonic turbine cascades. Preprint at https://doi.org/10.21203/rs.3.rs-4219258/v1 (2024).
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Shuai, Z. & Shen, L. Mitigating Heterogeneity in Federated Multimodal Learning with Biomedical Vision-Language Pre-training. (2024) http://doi.org/10.48550/ARXIV.2404.03854.
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Zyrianov, V., Che, H., Liu, Z. & Wang, S. LidarDM: Generative LiDAR Simulation in a Generated World. (2024) http://doi.org/10.48550/ARXIV.2404.02903.
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Tamirisa, R., Won, J., Lu, C., Arel, R. & Zhou, A. FedSelect: Customized Selection of Parameters for Fine-Tuning during Personalized Federated Learning. (2023) http://doi.org/10.48550/ARXIV.2306.13264.
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Most, E. R., Beloborodov, A. M. & Ripperda, B. Monster shocks, gamma-ray bursts and black hole quasi-normal modes from neutron-star collapse. (2024) http://doi.org/10.48550/ARXIV.2404.01456.
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Kim, Y., Most, E. R., Throwe, W., Teukolsky, S. A. & Deppe, N. General relativistic force-free electrodynamics with a discontinuous Galerkin-finite difference hybrid method. (2024) http://doi.org/10.48550/ARXIV.2404.01531.
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Mallinar, N., Zane, A., Frei, S. & Yu, B. Minimum-Norm Interpolation Under Covariate Shift. (2024) http://doi.org/10.48550/ARXIV.2404.00522.
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Han, J., Guzman, J. A. & Chu, M. L. Dynamic land cover evapotranspiration model algorithm: DyLEMa. Computers and Electronics in Agriculture 220, 108875 (2024).
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He, J., Koric, S., Abueidda, D., Najafi, A. & Jasiuk, I. Geom-DeepONet: A Point-cloud-based Deep Operator Network for Field Predictions on 3D Parameterized Geometries. (2024) http://doi.org/10.48550/ARXIV.2403.14788.
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Kushwaha, S. et al. Advanced Deep Operator Networks to Predict Multiphysics Solution Fields in Materials Processing and Additive Manufacturing. (2024) http://doi.org/10.48550/ARXIV.2403.14795.
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LaCour, R. A., Moore, T. C. & Glotzer, S. C. Tuning Stoichiometry to Promote Formation of Binary Colloidal Superlattices. Phys. Rev. Lett. 128, 188001 (2022).
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Kim, A. et al. Symmetry-breaking in patch formation on triangular gold nanoparticles by asymmetric polymer grafting. Nat Commun 13, 6774 (2022).
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Zhou, W. et al. Space-tiled colloidal crystals from DNA-forced shape-complementary polyhedra pairing. Science 383, 312–319 (2024).
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Lee, S. et al. Shape memory in self-adapting colloidal crystals. Nature 610, 674–679 (2022).
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Yang, S. et al. Self-Assembly of Atomically Aligned Nanoparticle Superlattices from Pt–Fe 3 O 4 Heterodimer Nanoparticles. J. Am. Chem. Soc. 145, 6280–6288 (2023).
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Votapka, L. W., Stokely, A. M., Ojha, A. A. & Amaro, R. E. SEEKR2: Versatile Multiscale Milestoning Utilizing the OpenMM Molecular Dynamics Engine. J. Chem. Inf. Model. 62, 3253–3262 (2022).
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Schönhöfer, P. W. A., Sun, K., Mao, X. & Glotzer, S. C. Rationalizing Euclidean Assemblies of Hard Polyhedra from Tessellations in Curved Space. Phys. Rev. Lett. 131, 258201 (2023).
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Yan, M. et al. Probing the Edges between Stability and Degradation of a Series of ZnSe‐Based Layered Hybrid Semiconductors. Adv Materials Inter 9, 2200347 (2022).
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Rivera-Rivera, L. Y., Moore, T. C. & Glotzer, S. C. Inverse design of triblock Janus spheres for self-assembly of complex structures in the crystallization slot via digital alchemy. Soft Matter 19, 2726–2736 (2023).
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Elbert, K. C. et al. Evaporation-Driven Coassembly of Hierarchical, Multicomponent Networks. ACS Nano 16, 4508–4516 (2022).
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Lee, S., Vo, T. & Glotzer, S. C. Entropy compartmentalization stabilizes open host–guest colloidal clathrates. Nat. Chem. 15, 905–912 (2023).
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Lee, S. & Glotzer, S. C. Entropically engineered formation of fivefold and icosahedral twinned clusters of colloidal shapes. Nat Commun 13, 7362 (2022).
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Lim, Y., Lee, S. & Glotzer, S. C. Engineering the Thermodynamic Stability and Metastability of Mesophases of Colloidal Bipyramids through Shape Entropy. ACS Nano 17, 4287–4295 (2023).
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Mathivanan, J., Bai, Z., Chen, A. & Sheng, J. Design, Synthesis, and Characterization of a Novel 2′–5′-Linked Amikacin-Binding Aptamer: An Experimental and MD Simulation Study. ACS Chem. Biol. 17, 3478–3488 (2022).
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Schönhöfer, P. W. A. & Glotzer, S. C. Curvature-controlled geometrical lensing behavior in self-propelled colloidal particle systems. Soft Matter 18, 8561–8571 (2022).
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Marino, E. et al. Crystallization of binary nanocrystal superlattices and the relevance of short-range attraction. Nat. Synth 3, 111–122 (2023).
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Cheng, L. et al. Cotranscriptional RNA strand exchange underlies the gene regulation mechanism in a purine-sensing transcriptional riboswitch. Nucleic Acids Research 50, 12001–12018 (2022).
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Lee, S. Y., Schönhöfer, P. W. A. & Glotzer, S. C. Complex motion of steerable vesicular robots filled with active colloidal rods. Sci Rep 13, 22773 (2023).
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Wang, Z.-Q. & Watanabe, S. UNSSOR: Unsupervised Neural Speech Separation by Leveraging Over-determined Training Mixtures. (2023) http://doi.org/10.48550/ARXIV.2305.20054.
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Tran, H. & Chew, H. B. Transient to steady-state morphology evolution of carbon surfaces under ion bombardment: Monte Carlo simulations. Acta Materialia 263, 119498 (2024).
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Abedsoltan, A., Belkin, M. & Pandit, P. Toward Large Kernel Models. (2023) http://doi.org/10.48550/ARXIV.2302.02605.
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Wang, Z.-Q. et al. TF-GridNet: Integrating Full- and Sub-Band Modeling for Speech Separation. IEEE/ACM Trans. Audio Speech Lang. Process. 31, 3221–3236 (2023).
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Subramanian, S., Balsara, D. S., Bhoriya, D. & Kumar, H. Techniques, Tricks, and Algorithms for Efficient GPU-Based Processing of Higher Order Hyperbolic PDEs. Commun. Appl. Math. Comput. (2023) http://doi.org/10.1007/s42967-022-00235-9.
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Tran, H. & Chew, H. B. Surface morphology and carbon structure effects on sputtering: Bridging scales between molecular dynamics simulations and experiments. Carbon 205, 180–193 (2023).
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Shon, S. et al. SLUE Phase-2: A Benchmark Suite of Diverse Spoken Language Understanding Tasks. in Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) 8906–8937 (Association for Computational Linguistics, Toronto, Canada, 2023). http://doi.org/10.18653/v1/2023.acl-long.496.
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Chen, W. et al. Joint Prediction and Denoising for Large-Scale Multilingual Self-Supervised Learning. in 2023 IEEE Automatic Speech Recognition and Understanding Workshop (ASRU) 1–8 (IEEE, Taipei, Taiwan, 2023). http://doi.org/10.1109/ASRU57964.2023.10389735.
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Peng, Y., Lee, J. & Watanabe, S. I3D: Transformer Architectures with Input-Dependent Dynamic Depth for Speech Recognition. in ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) 1–5 (IEEE, Rhodes Island, Greece, 2023). http://doi.org/10.1109/ICASSP49357.2023.10096662.
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Wei, W.-S. et al. Hierarchical assembly is more robust than egalitarian assembly in synthetic capsids. Proc. Natl. Acad. Sci. U.S.A. 121, e2312775121 (2024).
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Shi, J. et al. Exploration on HuBERT with Multiple Resolution. in INTERSPEECH 2023 3287–3291 (ISCA, 2023). http://doi.org/10.21437/Interspeech.2023-1337.
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Chang, X., Yan, B., Fujita, Y., Maekaku, T. & Watanabe, S. Exploration of Efficient End-to-End ASR using Discretized Input from Self-Supervised Learning. in INTERSPEECH 2023 1399–1403 (ISCA, 2023). http://doi.org/10.21437/Interspeech.2023-2051.
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Park, H. et al. End-to-end AI framework for interpretable prediction of molecular and crystal properties. Mach. Learn.: Sci. Technol. 4, 025036 (2023).
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Peng, Y., Sudo, Y., Muhammad, S. & Watanabe, S. DPHuBERT: Joint Distillation and Pruning of Self-Supervised Speech Models. in INTERSPEECH 2023 62–66 (ISCA, 2023). http://doi.org/10.21437/Interspeech.2023-1213.
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Luo, Y., Liu, Y. & Peng, J. Calibrated geometric deep learning improves kinase–drug binding predictions. Nat Mach Intell 5, 1390–1401 (2023).
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Tang, J., Chen, W., Chang, X., Watanabe, S. & MacWhinney, B. A New Benchmark of Aphasia Speech Recognition and Detection Based on E-Branchformer and Multi-task Learning. in INTERSPEECH 2023 1528–1532 (ISCA, 2023). http://doi.org/10.21437/Interspeech.2023-2191.
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Peng, Y. et al. A Comparative Study on E-Branchformer vs Conformer in Speech Recognition, Translation, and Understanding Tasks. in INTERSPEECH 2023 2208–2212 (ISCA, 2023). http://doi.org/10.21437/Interspeech.2023-1194.
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Luo, C., Sun, Y. & Wentzcovitch, R. M. Probing the state of hydrogen in δ − AlOOH at mantle conditions with machine learning potential. Phys. Rev. Research 6, 013292 (2024).
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Yang, Y., Pandey, A. & Wang, D. Towards Decoupling Frontend Enhancement and Backend Recognition in Monaural Robust ASR. Preprint at https://doi.org/10.48550/arXiv.2403.06387 (2024).
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Lozenski, L., Cam, R. M., Anastasio, M. A. & Villa, U. ProxNF: Neural Field Proximal Training for High-Resolution 4D Dynamic Image Reconstruction. (2024) http://doi.org/10.48550/ARXIV.2403.03860.
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Kalkhorani, V. A. & Wang, D. CrossNet: Leveraging Global, Cross-Band, Narrow-Band, and Positional Encoding for Single- and Multi-Channel Speaker Separation. (2024) http://doi.org/10.48550/ARXIV.2403.03411.

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