Marin Soljacic

76 papers A* 11Journal 54Unranked 11

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	A Framework for Closed-Loop Robotic Assembly, Alignment and Self-Recovery of Precision Optical Systems. CoRR Seou Choi, Sachin Vaidya, Caio Silva, Shiekh Zia Uddin, Sajib Biswas Shuvo, Shrish Choudhary, Marin Soljacic
2026	J	`jnl`	Active learning for photonics. CoRR Ryan Lopez, Charlotte Loh, Rumen Dangovski, Marin Soljacic
2026	J	`jnl`	Unsupervised Decomposition and Recombination with Discriminator-Driven Diffusion Models. CoRR Archer Wang, Emile Anand, Yilun Du, Marin Soljacic
2025	J	`jnl`	AI-Driven Robotics for Free-Space Optics. CoRR Shiekh Zia Uddin, Sachin Vaidya, Shrish Choudhary, Zhuo Chen, Raafat K. Salib, Luke Huang, Dirk R. Englund, Marin Soljacic
2025	A*	`conf`	KAN: Kolmogorov-Arnold Networks. ICLR Ziming Liu, Yixuan Wang, Sachin Vaidya, Fabian Ruehle, James Halverson, Marin Soljacic, Thomas Y. Hou, Max Tegmark
2025	J	`jnl`	L CoRR Zhuo Chen, Oriol Mayné i Comas, Zhuotao Jin, Di Luo, Marin Soljacic
2025	J	`jnl`	Learning simple heuristic rules for classifying materials based on chemical composition. CoRR Andrew Ma, Marin Soljacic
2025	J	`jnl`	Predicting band gap from chemical composition: A simple learned model for a material property with atypical statistics. CoRR Andrew Ma, Owen Dugan, Marin Soljacic
2024	—	`conf`	Data-Informed Global Sparseness in Attention Mechanisms for Deep Neural Networks. LREC/COLING Ileana Rugina, Rumen Dangovski, Li Jing, Preslav Nakov, Marin Soljacic
2024	J	`jnl`	Deep Learning and Symbolic Regression for Discovering Parametric Equations. IEEE Trans. Neural Networks Learn. Syst. Michael Zhang, Samuel Kim, Peter Y. Lu, Marin Soljacic
2024	J	`jnl`	KAN: Kolmogorov-Arnold Networks. CoRR Ziming Liu, Yixuan Wang, Sachin Vaidya, Fabian Ruehle, James Halverson, Marin Soljacic, Thomas Y. Hou, Max Tegmark
2024	A*	`conf`	OccamLLM: Fast and Exact Language Model Arithmetic in a Single Step. NeurIPS Owen Dugan, Donato Jiménez-Benetó, Charlotte Loh, Zhuo Chen, Rumen Dangovski, Marin Soljacic
2024	J	`jnl`	OccamLLM: Fast and Exact Language Model Arithmetic in a Single Step. CoRR Owen Dugan, Donato Manuel Jimenez Beneto, Charlotte Loh, Zhuo Chen, Rumen Dangovski, Marin Soljacic
2024	A*	`conf`	QuanTA: Efficient High-Rank Fine-Tuning of LLMs with Quantum-Informed Tensor Adaptation. NeurIPS Zhuo Chen, Rumen Dangovski, Charlotte Loh, Owen Dugan, Di Luo, Marin Soljacic
2024	J	`jnl`	QuanTA: Efficient High-Rank Fine-Tuning of LLMs with Quantum-Informed Tensor Adaptation. CoRR Zhuo Chen, Rumen Dangovski, Charlotte Loh, Owen Dugan, Di Luo, Marin Soljacic
2024	J	`jnl`	Stochastic logic in biased coupled photonic probabilistic bits. CoRR Michael Horodynski, Charles Roques-Carmes, Yannick Salamin, Seou Choi, Jamison Sloan, Di Luo, Marin Soljacic
2024	A*	`conf`	TENG: Time-Evolving Natural Gradient for Solving PDEs With Deep Neural Nets Toward Machine Precision. ICML Zhuo Chen, Jacob McCarran, Esteban Vizcaino, Marin Soljacic, Di Luo
2024	J	`jnl`	TENG: Time-Evolving Natural Gradient for Solving PDEs with Deep Neural Net. CoRR Zhuo Chen, Jacob McCarran, Esteban Vizcaino, Marin Soljacic, Di Luo
2023	A*	`conf`	ANTN: Bridging Autoregressive Neural Networks and Tensor Networks for Quantum Many-Body Simulation. NeurIPS Zhuo Chen, Laker Newhouse, Eddie Chen, Di Luo, Marin Soljacic
2023	—	`conf`	Asymmetric Grouped Convolutions for Logarithmic Scale Efficient Convolutional Neural Networks. HPEC Li Jing, Rumen Dangovski, Marin Soljacic
2023	J	`jnl`	Autoregressive Neural TensorNet: Bridging Neural Networks and Tensor Networks for Quantum Many-Body Simulation. CoRR Zhuo Chen, Laker Newhouse, Eddie Chen, Di Luo, Marin Soljacic
2023	—	`conf`	Contextualizing Enhances Gradient Based Meta Learning for Few Shot Image Classification. HPEC Evan Vogelbaum, Rumen Dangovski, Li Jing, Marin Soljacic
2023	J	`jnl`	Geometry of contact: contact planning for multi-legged robots via spin models duality. CoRR Baxi Chong, Di Luo, Tianyu Wang, Gabriel B. Margolis, Juntao He, Pulkit Agrawal, Marin Soljacic, Daniel I. Goldman
2023	J	`jnl`	Learning to Optimize Quasi-Newton Methods. Trans. Mach. Learn. Res. Isaac Liao, Rumen Dangovski, Jakob Nicolaus Foerster, Marin Soljacic
2023	—	`conf`	Manifold Transfer Networks for Lens Distortion Rectification. HPEC Li Jing, Lay Jain, Rumen Dangovski, Marin Soljacic
2023	—	`conf`	Meta-Learning and Self-Supervised Pretraining for Storm Event Imagery Translation. HPEC Ileana Rugina, Rumen Dangovski, Mark Veillette, Pooya Khorrami, Brian Cheung, Olga Simek, Marin Soljacic
2023	J	`jnl`	Mitigating Confirmation Bias in Semi-supervised Learning via Efficient Bayesian Model Averaging. Trans. Mach. Learn. Res. Charlotte Loh, Rumen Dangovski, Shivchander Sudalairaj, Seungwook Han, Ligong Han, Leonid Karlinsky, Marin Soljacic, Akash Srivastava
2023	J	`jnl`	Model Stitching: Looking For Functional Similarity Between Representations. CoRR Adriano Hernandez, Rumen Dangovski, Peter Y. Lu, Marin Soljacic
2023	A*	`conf`	Multi-Symmetry Ensembles: Improving Diversity and Generalization via Opposing Symmetries. ICML Charlotte Loh, Seungwook Han, Shivchander Sudalairaj, Rumen Dangovski, Kai Xu, Florian Wenzel, Marin Soljacic, Akash Srivastava
2023	J	`jnl`	Multi-Symmetry Ensembles: Improving Diversity and Generalization via Opposing Symmetries. CoRR Charlotte Loh, Seungwook Han, Shivchander Sudalairaj, Rumen Dangovski, Kai Xu, Florian Wenzel, Marin Soljacic, Akash Srivastava
2023	J	`jnl`	Multimodal Learning for Crystalline Materials. CoRR Viggo Moro, Charlotte Loh, Rumen Dangovski, Ali Ghorashi, Andrew Ma, Zhuo Chen, Peter Y. Lu, Thomas Christensen, Marin Soljacic
2023	A*	`conf`	Q-Flow: Generative Modeling for Differential Equations of Open Quantum Dynamics with Normalizing Flows. ICML Owen M. Dugan, Peter Y. Lu, Rumen Dangovski, Di Luo, Marin Soljacic
2023	J	`jnl`	Q-Flow: Generative Modeling for Differential Equations of Open Quantum Dynamics with Normalizing Flows. CoRR Owen Dugan, Peter Y. Lu, Rumen Dangovski, Di Luo, Marin Soljacic
2023	A*	`conf`	QuACK: Accelerating Gradient-Based Quantum Optimization with Koopman Operator Learning. NeurIPS Di Luo, Jiayu Shen, Rumen Dangovski, Marin Soljacic
2022	J	`jnl`	AI-Assisted Discovery of Quantitative and Formal Models in Social Science. CoRR Julia Balla, Sihao Huang, Owen Dugan, Rumen Dangovski, Marin Soljacic
2022	J	`jnl`	Deep Learning and Symbolic Regression for Discovering Parametric Equations. CoRR Michael Zhang, Samuel Kim, Peter Y. Lu, Marin Soljacic
2022	J	`jnl`	Deep Learning for Bayesian Optimization of Scientific Problems with High-Dimensional Structure. Trans. Mach. Learn. Res. Samuel Kim, Peter Y. Lu, Charlotte Loh, Jamie Smith, Jasper Snoek, Marin Soljacic
2022	—	`conf`	DiffCSE: Difference-based Contrastive Learning for Sentence Embeddings. NAACL-HLT Yung-Sung Chuang, Rumen Dangovski, Hongyin Luo, Yang Zhang, Shiyu Chang, Marin Soljacic, Shang-wen Li, Scott Yih, Yoon Kim, James R. Glass
2022	J	`jnl`	DiffCSE: Difference-based Contrastive Learning for Sentence Embeddings. CoRR Yung-Sung Chuang, Rumen Dangovski, Hongyin Luo, Yang Zhang, Shiyu Chang, Marin Soljacic, Shang-wen Li, Wen-tau Yih, Yoon Kim, James R. Glass
2022	J	`jnl`	Discovering Conservation Laws using Optimal Transport and Manifold Learning. CoRR Peter Y. Lu, Rumen Dangovski, Marin Soljacic
2022	A*	`conf`	Equivariant Self-Supervised Learning: Encouraging Equivariance in Representations. ICLR Rumen Dangovski, Li Jing, Charlotte Loh, Seungwook Han, Akash Srivastava, Brian Cheung, Pulkit Agrawal, Marin Soljacic
2022	J	`jnl`	Koopman Operator learning for Accelerating Quantum Optimization and Machine Learning. CoRR Di Luo, Jiayu Shen, Rumen Dangovski, Marin Soljacic
2022	J	`jnl`	Learning to Optimize Quasi-Newton Methods. CoRR Isaac Liao, Rumen R. Dangovski, Jakob N. Foerster, Marin Soljacic
2022	J	`jnl`	On the Importance of Calibration in Semi-supervised Learning. CoRR Charlotte Loh, Rumen Dangovski, Shivchander Sudalairaj, Seungwook Han, Ligong Han, Leonid Karlinsky, Marin Soljacic, Akash Srivastava
2022	J	`jnl`	Topogivity: A Machine-Learned Chemical Rule for Discovering Topological Materials. CoRR Andrew Ma, Yang Zhang, Thomas Christensen, Hoi Chun Po, Li Jing, Liang Fu, Marin Soljacic
2021	—	`conf`	Adapting Deep Learning Models to New Meteorological Contexts Using Transfer Learning. IEEE BigData Pooya Khorrami, Olga Simek, Brian Cheung, Mark Veillette, Rumen Dangovski, Ileana Rugina, Marin Soljacic, Pulkit Agrawal
2021	J	`jnl`	Discovering Sparse Interpretable Dynamics from Partial Observations. CoRR Peter Y. Lu, Joan Ariño, Marin Soljacic
2021	J	`jnl`	Equivariant Contrastive Learning. CoRR Rumen Dangovski, Li Jing, Charlotte Loh, Seungwook Han, Akash Srivastava, Brian Cheung, Pulkit Agrawal, Marin Soljacic
2021	J	`jnl`	Integration of Neural Network-Based Symbolic Regression in Deep Learning for Scientific Discovery. IEEE Trans. Neural Networks Learn. Syst. Samuel Kim, Peter Y. Lu, Srijon Mukherjee, Michael Gilbert, Li Jing, Vladimir Ceperic, Marin Soljacic
2021	J	`jnl`	Meta-Learning and Self-Supervised Pretraining for Real World Image Translation. CoRR Ileana Rugina, Rumen Dangovski, Mark Veillette, Pooya Khorrami, Brian Cheung, Olga Simek, Marin Soljacic
2021	—	`conf`	Non-Abelian gauge fields with fiber optics and beyond. OFC Yi Yang, Marin Soljacic
2021	J	`jnl`	Scalable and Flexible Deep Bayesian Optimization with Auxiliary Information for Scientific Problems. CoRR Samuel Kim, Peter Y. Lu, Charlotte Loh, Jamie Smith, Jasper Snoek, Marin Soljacic
2021	J	`jnl`	Surrogate- and invariance-boosted contrastive learning for data-scarce applications in science. CoRR Charlotte Loh, Thomas Christensen, Rumen Dangovski, Samuel Kim, Marin Soljacic
2021	A*	`conf`	We Can Explain Your Research in Layman's Terms: Towards Automating Science Journalism at Scale. AAAI Rumen Dangovski, Michelle Shen, Dawson Byrd, Li Jing, Desislava Tsvetkova, Preslav Nakov, Marin Soljacic
2020	J	`jnl`	Contextualizing Enhances Gradient Based Meta Learning. CoRR Evan Vogelbaum, Rumen Dangovski, Li Jing, Marin Soljacic
2020	J	`jnl`	Data-Informed Global Sparseness in Attention Mechanisms for Deep Neural Networks. CoRR Ileana Rugina, Rumen Dangovski, Li Jing, Preslav Nakov, Marin Soljacic
2020	J	`jnl`	Interpretable Neuroevolutionary Models for Learning Non-Differentiable Functions and Programs. CoRR Allan dos Santos Costa, Rumen Dangovski, Samuel Kim, Pawan Goyal, Marin Soljacic, Joseph Jacobson
2020	J	`jnl`	On a Novel Application of Wasserstein-Procrustes for Unsupervised Cross-Lingual Learning. CoRR Guillem Ramírez, Rumen Dangovski, Preslav Nakov, Marin Soljacic
2019	J	`jnl`	Extracting Interpretable Physical Parameters from Spatiotemporal Systems using Unsupervised Learning. CoRR Peter Y. Lu, Samuel Kim, Marin Soljacic
2019	J	`jnl`	Gated Orthogonal Recurrent Units: On Learning to Forget. Neural Comput. Li Jing, Çaglar Gülçehre, John Peurifoy, Yichen Shen, Max Tegmark, Marin Soljacic, Yoshua Bengio
2019	J	`jnl`	Integration of Neural Network-Based Symbolic Regression in Deep Learning for Scientific Discovery. CoRR Samuel Kim, Peter Y. Lu, Srijon Mukherjee, Michael Gilbert, Li Jing, Vladimir Ceperic, Marin Soljacic
2019	J	`jnl`	Rotational Unit of Memory: A Novel Representation Unit for RNNs with Scalable Applications. Trans. Assoc. Comput. Linguistics Rumen Dangovski, Li Jing, Preslav Nakov, Mico Tatalovic, Marin Soljacic
2018	—	`conf`	Controlling the Near-Field of Metasurfaces for Free-Electron Multi-Harmonic Hard X-Ray Generation. ICTON Gilles Rosolen, Liang Jie Wong, Nicholas Rivera, Bjorn Maes, Marin Soljacic, Ido Kaminer
2018	—	`conf`	Gated Orthogonal Recurrent Units: On Learning to Forget. AAAI Workshops Li Jing, Çaglar Gülçehre, John Peurifoy, Yichen Shen, Max Tegmark, Marin Soljacic, Yoshua Bengio
2018	J	`jnl`	Large-Scale Optical Neural Networks based on Photoelectric Multiplication. CoRR Ryan Hamerly, Alex Sludds, Liane Bernstein, Marin Soljacic, Dirk R. Englund
2018	J	`jnl`	Migrating Knowledge between Physical Scenarios based on Artificial Neural Networks. CoRR Yurui Qu, Li Jing, Yichen Shen, Min Qiu, Marin Soljacic
2018	J	`jnl`	On-Chip Optical Convolutional Neural Networks. CoRR Hengameh Bagherian, Scott A. Skirlo, Yichen Shen, Huaiyu Meng, Vladimir Ceperic, Marin Soljacic
2018	J	`jnl`	Photonic Recurrent Ising Sampler. CoRR 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
2018	—	`conf`	Rotational Unit of Memory. ICLR (Workshop) Rumen Dangovski, Li Jing, Marin Soljacic
2018	J	`jnl`	WaveletNet: Logarithmic Scale Efficient Convolutional Neural Networks for Edge Devices. CoRR Li Jing, Rumen Dangovski, Marin Soljacic
2017	J	`jnl`	Gated Orthogonal Recurrent Units: On Learning to Forget. CoRR Li Jing, Çaglar Gülçehre, John Peurifoy, Yichen Shen, Max Tegmark, Marin Soljacic, Yoshua Bengio
2017	J	`jnl`	Rotational Unit of Memory. CoRR Rumen Dangovski, Li Jing, Marin Soljacic
2017	A*	`conf`	Tunable Efficient Unitary Neural Networks (EUNN) and their application to RNNs. ICML Li Jing, Yichen Shen, Tena Dubcek, John Peurifoy, Scott A. Skirlo, Yann LeCun, Max Tegmark, Marin Soljacic
2016	J	`jnl`	Tunable Efficient Unitary Neural Networks (EUNN) and their application to RNN. CoRR Li Jing, Yichen Shen, Tena Dubcek, John Peurifoy, Scott A. Skirlo, Max Tegmark, Marin Soljacic
2014	J	`jnl`	Binary matrices of optimal autocorrelations as alignment marks. CoRR Scott A. Skirlo, Ling Lu, Marin Soljacic
2013	J	`jnl`	Plasmons in Graphene: Fundamental Properties and Potential Applications. Proc. IEEE Marinko Jablan, Marin Soljacic, Hrvoje Buljan