default search action
Marin Soljacic
Person information
Refine list
refinements active!
zoomed in on ?? of ?? records
view refined list in
export refined list as
2020 – today
- 2024
- [j8]Michael Zhang, Samuel Kim
, Peter Y. Lu
Deep Learning and Symbolic Regression for Discovering Parametric Equations. IEEE Trans. Neural Networks Learn. Syst. 35(11): 16775-16787 (2024) - [c19]Ileana Rugina, Rumen Dangovski, Li Jing, Preslav Nakov, Marin Soljacic:
Data-Informed Global Sparseness in Attention Mechanisms for Deep Neural Networks. LREC/COLING 2024: 4392-4403 - [c18]Zhuo Chen, Jacob McCarran, Esteban Vizcaino, Marin Soljacic, Di Luo:
TENG: Time-Evolving Natural Gradient for Solving PDEs With Deep Neural Nets Toward Machine Precision. ICML 2024 - [i39]Zhuo Chen, Jacob McCarran, Esteban Vizcaino, Marin Soljacic, Di Luo:
TENG: Time-Evolving Natural Gradient for Solving PDEs with Deep Neural Net. CoRR abs/2404.10771 (2024) - [i38]Ziming Liu, Yixuan Wang, Sachin Vaidya, Fabian Ruehle, James Halverson, Marin Soljacic, Thomas Y. Hou, Max Tegmark:
KAN: Kolmogorov-Arnold Networks. CoRR abs/2404.19756 (2024) - [i37]Zhuo Chen, Rumen Dangovski, Charlotte Loh, Owen Dugan, Di Luo, Marin Soljacic:
QuanTA: Efficient High-Rank Fine-Tuning of LLMs with Quantum-Informed Tensor Adaptation. CoRR abs/2406.00132 (2024) - [i36]Michael Horodynski
Stochastic logic in biased coupled photonic probabilistic bits. CoRR abs/2406.04000 (2024) - [i35]Owen Dugan, Donato Manuel Jimenez Beneto, Charlotte Loh, Zhuo Chen, Rumen Dangovski, Marin Soljacic:
OccamLLM: Fast and Exact Language Model Arithmetic in a Single Step. CoRR abs/2406.06576 (2024) - 2023
- [j7]Isaac Liao, Rumen Dangovski, Jakob Nicolaus Foerster, Marin Soljacic:
Learning to Optimize Quasi-Newton Methods. Trans. Mach. Learn. Res. 2023 (2023) - [j6]Charlotte Loh, Rumen Dangovski, Shivchander Sudalairaj, Seungwook Han, Ligong Han, Leonid Karlinsky, Marin Soljacic, Akash Srivastava:
Mitigating Confirmation Bias in Semi-supervised Learning via Efficient Bayesian Model Averaging. Trans. Mach. Learn. Res. 2023 (2023) - [c17]Li Jing, Rumen Dangovski, Marin Soljacic:
Asymmetric Grouped Convolutions for Logarithmic Scale Efficient Convolutional Neural Networks. HPEC 2023: 1-12 - [c16]Li Jing, Lay Jain, Rumen Dangovski, Marin Soljacic:
Manifold Transfer Networks for Lens Distortion Rectification. HPEC 2023: 1-8 - [c15]Ileana Rugina, Rumen Dangovski, Mark Veillette, Pooya Khorrami, Brian Cheung, Olga Simek, Marin Soljacic:
Meta-Learning and Self-Supervised Pretraining for Storm Event Imagery Translation. HPEC 2023: 1-9 - [c14]Evan Vogelbaum, Rumen Dangovski, Li Jing, Marin Soljacic:
Contextualizing Enhances Gradient Based Meta Learning for Few Shot Image Classification. HPEC 2023: 1-13 - [c13]Owen M. Dugan, Peter Y. Lu, Rumen Dangovski, Di Luo, Marin Soljacic:
Q-Flow: Generative Modeling for Differential Equations of Open Quantum Dynamics with Normalizing Flows. ICML 2023: 8879-8901 - [c12]Charlotte Loh, Seungwook Han, Shivchander Sudalairaj, Rumen Dangovski, Kai Xu, Florian Wenzel, Marin Soljacic, Akash Srivastava:
Multi-Symmetry Ensembles: Improving Diversity and Generalization via Opposing Symmetries. ICML 2023: 22614-22630 - [c11]Zhuo Chen, Laker Newhouse, Eddie Chen, Di Luo, Marin Soljacic:
ANTN: Bridging Autoregressive Neural Networks and Tensor Networks for Quantum Many-Body Simulation. NeurIPS 2023 - [c10]Di Luo, Jiayu Shen, Rumen Dangovski, Marin Soljacic:
QuACK: Accelerating Gradient-Based Quantum Optimization with Koopman Operator Learning. NeurIPS 2023 - [i34]Baxi Chong, Di Luo, Tianyu Wang, Gabriel B. Margolis, Juntao He, Pulkit Agrawal, Marin Soljacic, Daniel I. Goldman:
Geometry of contact: contact planning for multi-legged robots via spin models duality. CoRR abs/2302.03019 (2023) - [i33]Owen Dugan, Peter Y. Lu, Rumen Dangovski, Di Luo, Marin Soljacic:
Q-Flow: Generative Modeling for Differential Equations of Open Quantum Dynamics with Normalizing Flows. CoRR abs/2302.12235 (2023) - [i32]Charlotte Loh, Seungwook Han, Shivchander Sudalairaj, Rumen Dangovski, Kai Xu, Florian Wenzel, Marin Soljacic, Akash Srivastava:
Multi-Symmetry Ensembles: Improving Diversity and Generalization via Opposing Symmetries. CoRR abs/2303.02484 (2023) - [i31]Adriano Hernandez, Rumen Dangovski, Peter Y. Lu, Marin Soljacic:
Model Stitching: Looking For Functional Similarity Between Representations. CoRR abs/2303.11277 (2023) - [i30]Zhuo Chen, Laker Newhouse, Eddie Chen, Di Luo, Marin Soljacic:
Autoregressive Neural TensorNet: Bridging Neural Networks and Tensor Networks for Quantum Many-Body Simulation. CoRR abs/2304.01996 (2023) - [i29]Viggo Moro, Charlotte Loh, Rumen Dangovski, Ali Ghorashi, Andrew Ma, Zhuo Chen, Peter Y. Lu, Thomas Christensen, Marin Soljacic:
Multimodal Learning for Crystalline Materials. CoRR abs/2312.00111 (2023) - 2022
- [j5]Samuel Kim, Peter Y. Lu
Deep Learning for Bayesian Optimization of Scientific Problems with High-Dimensional Structure. Trans. Mach. Learn. Res. 2022 (2022) - [c9]Rumen Dangovski, Li Jing, Charlotte Loh, Seungwook Han, Akash Srivastava, Brian Cheung, Pulkit Agrawal, Marin Soljacic:
Equivariant Self-Supervised Learning: Encouraging Equivariance in Representations. ICLR 2022 - [c8]Yung-Sung Chuang, Rumen Dangovski, Hongyin Luo, Yang Zhang, Shiyu Chang, Marin Soljacic, Shang-Wen Li, Scott Yih, Yoon Kim, James R. Glass:
DiffCSE: Difference-based Contrastive Learning for Sentence Embeddings. NAACL-HLT 2022: 4207-4218 - [i28]Andrew Ma, Yang Zhang, Thomas Christensen, Hoi Chun Po, Li Jing, Liang Fu, Marin Soljacic:
Topogivity: A Machine-Learned Chemical Rule for Discovering Topological Materials. CoRR abs/2202.05255 (2022) - [i27]Yung-Sung Chuang
DiffCSE: Difference-based Contrastive Learning for Sentence Embeddings. CoRR abs/2204.10298 (2022) - [i26]Michael Zhang, Samuel Kim, Peter Y. Lu, Marin Soljacic:
Deep Learning and Symbolic Regression for Discovering Parametric Equations. CoRR abs/2207.00529 (2022) - [i25]Peter Y. Lu, Rumen Dangovski, Marin Soljacic:
Discovering Conservation Laws using Optimal Transport and Manifold Learning. CoRR abs/2208.14995 (2022) - [i24]Julia Balla, Sihao Huang, Owen Dugan, Rumen Dangovski, Marin Soljacic:
AI-Assisted Discovery of Quantitative and Formal Models in Social Science. CoRR abs/2210.00563 (2022) - [i23]Charlotte Loh, Rumen Dangovski, Shivchander Sudalairaj, Seungwook Han, Ligong Han, Leonid Karlinsky, Marin Soljacic, Akash Srivastava:
On the Importance of Calibration in Semi-supervised Learning. CoRR abs/2210.04783 (2022) - [i22]Isaac Liao, Rumen R. Dangovski, Jakob N. Foerster, Marin Soljacic:
Learning to Optimize Quasi-Newton Methods. CoRR abs/2210.06171 (2022) - [i21]Di Luo, Jiayu Shen, Rumen Dangovski, Marin Soljacic:
Koopman Operator learning for Accelerating Quantum Optimization and Machine Learning. CoRR abs/2211.01365 (2022) - 2021
- [j4]Samuel Kim
Integration of Neural Network-Based Symbolic Regression in Deep Learning for Scientific Discovery. IEEE Trans. Neural Networks Learn. Syst. 32(9): 4166-4177 (2021) - [c7]Rumen Dangovski, Michelle Shen, Dawson Byrd, Li Jing, Desislava Tsvetkova, Preslav Nakov, Marin Soljacic:
We Can Explain Your Research in Layman's Terms: Towards Automating Science Journalism at Scale. AAAI 2021: 12728-12737 - [c6]Pooya Khorrami, Olga Simek, Brian Cheung, Mark Veillette, Rumen Dangovski, Ileana Rugina, Marin Soljacic, Pulkit Agrawal:
Adapting Deep Learning Models to New Meteorological Contexts Using Transfer Learning. IEEE BigData 2021: 4169-4177 - [c5]Yi Yang, Marin Soljacic:
Non-Abelian gauge fields with fiber optics and beyond. OFC 2021: 1-3 - [i20]Samuel Kim, Peter Y. Lu
Scalable and Flexible Deep Bayesian Optimization with Auxiliary Information for Scientific Problems. CoRR abs/2104.11667 (2021) - [i19]Peter Y. Lu
Discovering Sparse Interpretable Dynamics from Partial Observations. CoRR abs/2107.10879 (2021) - [i18]Charlotte Loh, Thomas Christensen
Surrogate- and invariance-boosted contrastive learning for data-scarce applications in science. CoRR abs/2110.08406 (2021) - [i17]Rumen Dangovski, Li Jing, Charlotte Loh, Seungwook Han, Akash Srivastava, Brian Cheung, Pulkit Agrawal, Marin Soljacic:
Equivariant Contrastive Learning. CoRR abs/2111.00899 (2021) - [i16]Ileana Rugina, Rumen Dangovski, Mark Veillette, Pooya Khorrami, Brian Cheung, Olga Simek, Marin Soljacic:
Meta-Learning and Self-Supervised Pretraining for Real World Image Translation. CoRR abs/2112.11929 (2021) - 2020
- [i15]Guillem Ramírez, Rumen Dangovski, Preslav Nakov, Marin Soljacic:
On a Novel Application of Wasserstein-Procrustes for Unsupervised Cross-Lingual Learning. CoRR abs/2007.09456 (2020) - [i14]Evan Vogelbaum, Rumen Dangovski, Li Jing, Marin Soljacic:
Contextualizing Enhances Gradient Based Meta Learning. CoRR abs/2007.10143 (2020) - [i13]Allan dos Santos Costa, Rumen Dangovski, Samuel Kim, Pawan Goyal, Marin Soljacic, Joseph Jacobson:
Interpretable Neuroevolutionary Models for Learning Non-Differentiable Functions and Programs. CoRR abs/2007.10784 (2020) - [i12]Ileana Rugina, Rumen Dangovski, Li Jing, Preslav Nakov, Marin Soljacic:
Data-Informed Global Sparseness in Attention Mechanisms for Deep Neural Networks. CoRR abs/2012.02030 (2020)
2010 – 2019
- 2019
- [j3]Li Jing, Çaglar Gülçehre
Gated Orthogonal Recurrent Units: On Learning to Forget. Neural Comput. 31(4) (2019) - [j2]Rumen Dangovski, Li Jing, Preslav Nakov, Mico Tatalovic
Rotational Unit of Memory: A Novel Representation Unit for RNNs with Scalable Applications. Trans. Assoc. Comput. Linguistics 7: 121-138 (2019) - [i11]Peter Y. Lu, Samuel Kim, Marin Soljacic:
Extracting Interpretable Physical Parameters from Spatiotemporal Systems using Unsupervised Learning. CoRR abs/1907.06011 (2019) - [i10]Samuel Kim, Peter Y. Lu, Srijon Mukherjee, Michael Gilbert, Li Jing, Vladimir Ceperic, Marin Soljacic:
Integration of Neural Network-Based Symbolic Regression in Deep Learning for Scientific Discovery. CoRR abs/1912.04825 (2019) - 2018
- [c4]Li Jing, Çaglar Gülçehre, John Peurifoy, Yichen Shen, Max Tegmark, Marin Soljacic, Yoshua Bengio:
Gated Orthogonal Recurrent Units: On Learning to Forget. AAAI Workshops 2018: 720-726 - [c3]Rumen Dangovski, Li Jing, Marin Soljacic:
Rotational Unit of Memory. ICLR (Workshop) 2018 - [c2]Gilles Rosolen, Liang Jie Wong, Nicholas Rivera, Bjorn Maes, Marin Soljacic, Ido Kaminer:
Controlling the Near-Field of Metasurfaces for Free-Electron Multi-Harmonic Hard X-Ray Generation. ICTON 2018: 1-4 - [i9]Hengameh Bagherian, Scott A. Skirlo, Yichen Shen, Huaiyu Meng, Vladimir Ceperic, Marin Soljacic:
On-Chip Optical Convolutional Neural Networks. CoRR abs/1808.03303 (2018) - [i8]Yurui Qu, Li Jing, Yichen Shen, Min Qiu, Marin Soljacic:
Migrating Knowledge between Physical Scenarios based on Artificial Neural Networks. CoRR abs/1809.00972 (2018) - [i7]Charles Roques-Carmes, Yichen Shen, Cristian Zanoci, Mihika Prabhu, Fadi Atieh, Li Jing, Tena Dubcek, Vladimir Ceperic, John D. Joannopoulos, Dirk R. Englund, Marin Soljacic:
Photonic Recurrent Ising Sampler. CoRR abs/1811.02705 (2018) - [i6]Li Jing, Rumen Dangovski, Marin Soljacic:
WaveletNet: Logarithmic Scale Efficient Convolutional Neural Networks for Edge Devices. CoRR abs/1811.11644 (2018) - [i5]Ryan Hamerly, Alex Sludds, Liane Bernstein, Marin Soljacic, Dirk R. Englund:
Large-Scale Optical Neural Networks based on Photoelectric Multiplication. CoRR abs/1812.07614 (2018) - 2017
- [c1]Li Jing, Yichen Shen, Tena Dubcek, John Peurifoy, Scott A. Skirlo, Yann LeCun, Max Tegmark, Marin Soljacic:
Tunable Efficient Unitary Neural Networks (EUNN) and their application to RNNs. ICML 2017: 1733-1741 - [i4]Li Jing, Çaglar Gülçehre, John Peurifoy, Yichen Shen, Max Tegmark, Marin Soljacic, Yoshua Bengio:
Gated Orthogonal Recurrent Units: On Learning to Forget. CoRR abs/1706.02761 (2017) - [i3]Rumen Dangovski, Li Jing, Marin Soljacic:
Rotational Unit of Memory. CoRR abs/1710.09537 (2017) - 2016
- [i2]Li Jing, Yichen Shen, Tena Dubcek, John Peurifoy, Scott A. Skirlo, Max Tegmark, Marin Soljacic:
Tunable Efficient Unitary Neural Networks (EUNN) and their application to RNN. CoRR abs/1612.05231 (2016) - 2014
- [i1]Scott A. Skirlo, Ling Lu, Marin Soljacic:
Binary matrices of optimal autocorrelations as alignment marks. CoRR abs/1408.6915 (2014) - 2013
- [j1]Marinko Jablan, Marin Soljacic, Hrvoje Buljan
Plasmons in Graphene: Fundamental Properties and Potential Applications. Proc. IEEE 101(7): 1689-1704 (2013)
Coauthor Index
aka: Rumen R. Dangovski
manage site settings
To protect your privacy, all features that rely on external API calls from your browser are turned off by default. You need to opt-in for them to become active. All settings here will be stored as cookies with your web browser. For more information see our F.A.Q.
Unpaywalled article links
Add open access links from to the list of external document links (if available).
Privacy notice: By enabling the option above, your browser will contact the API of unpaywall.org to load hyperlinks to open access articles. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Unpaywall privacy policy.
Archived links via Wayback Machine
For web page which are no longer available, try to retrieve content from the of the Internet Archive (if available).
Privacy notice: By enabling the option above, your browser will contact the API of archive.org to check for archived content of web pages that are no longer available. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Internet Archive privacy policy.
Reference lists
Add a list of references from ,
, and
to record detail pages.
load references from crossref.org and opencitations.net
Privacy notice: By enabling the option above, your browser will contact the APIs of crossref.org, opencitations.net, and semanticscholar.org to load article reference information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Crossref privacy policy and the OpenCitations privacy policy, as well as the AI2 Privacy Policy covering Semantic Scholar.
Citation data
Add a list of citing articles from and
to record detail pages.
load citations from opencitations.net
Privacy notice: By enabling the option above, your browser will contact the API of opencitations.net and semanticscholar.org to load citation information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the OpenCitations privacy policy as well as the AI2 Privacy Policy covering Semantic Scholar.
OpenAlex data
Load additional information about publications from .
Privacy notice: By enabling the option above, your browser will contact the API of openalex.org to load additional information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the information given by OpenAlex.
last updated on 2024-12-02 21:23 CET by the dblp team
all metadata released as open data under CC0 1.0 license
see also: Terms of Use | Privacy Policy | Imprint
dblp was originally created in 1993 at:
since 2018, dblp has been operated and maintained by:
the dblp computer science bibliography is funded and supported by: