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2020 – today
- 2024
[j8]Michael Zhang, Samuel Kim, Peter Y. Lu, Marin Soljacic:
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
, Charles Roques-Carmes, Yannick Salamin, Seou Choi, Jamison Sloan, Di Luo, Marin Soljacic:
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, Charlotte Loh, Jamie Smith, Jasper Snoek, Marin Soljacic:
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, Rumen Dangovski, Hongyin Luo, Yang Zhang, Shiyu Chang, Marin Soljacic, Shang-Wen Li, Wen-tau Yih, Yoon Kim, James R. Glass:
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, 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. 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, Charlotte Loh, Jamie Smith, Jasper Snoek, Marin Soljacic:
Scalable and Flexible Deep Bayesian Optimization with Auxiliary Information for Scientific Problems. CoRR abs/2104.11667 (2021) - [i19]Peter Y. Lu, Joan Ariño, Marin Soljacic:
Discovering Sparse Interpretable Dynamics from Partial Observations. CoRR abs/2107.10879 (2021) - [i18]Charlotte Loh, Thomas Christensen, Rumen Dangovski, Samuel Kim, Marin Soljacic:
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, John Peurifoy, Yichen Shen, Max Tegmark, Marin Soljacic, Yoshua Bengio:
Gated Orthogonal Recurrent Units: On Learning to Forget. Neural Comput. 31(4) (2019) - [j2]Rumen Dangovski, Li Jing, Preslav Nakov, Mico Tatalovic, Marin Soljacic:
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
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