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Publications

Complete list of publications on my Scholar Page

2024

  • Mali, A., Salvatori, T., & Ororbia, A. (2024). Tight Stability, Convergence, and Robustness Bounds for Predictive Coding Networks. arXiv preprint arXiv:2410.04708.

  • Das, S., & Mali, A. (2024). Exploring Learnability in Memory-Augmented Recurrent Neural Networks: Precision, Stability, and Empirical Insights. arXiv preprint arXiv:2410.03154.

  • Dave, N., Kifer, D., Giles, L., & Mali, A. (2024). Precision, Stability, and Generalization: A Comprehensive Assessment of RNNs learnability capability for Classifying Counter and Dyck Languages. arXiv preprint arXiv:2410.03118.

  • Sharma, A. S., Sarkar, N., Chundawat, V., Mali, A. A., & Mandal, M. (2024). Unlearning or concealment? a critical analysis and evaluation metrics for unlearning in diffusion models. arXiv preprint arXiv:2409.05668.

  • Chatterjee, R., Chundawat, V., Tarun, A., Mali, A., & Mandal, M. (2024). A unified framework for continual learning and machine unlearning. arXiv preprint arXiv:2408.11374.

  • Dave, N., Kifer, D., Giles, C. L., & Mali, A. (2024). Investigating Symbolic Capabilities of Large Language Models. arXiv preprint arXiv:2405.13209.

  • Yu, P., Mali, A., Velaga, T., Bi, A., Yu, J., Marone, C., ... & Elsworth, D. (2024). Crustal permeability generated through microearthquakes is constrained by seismic moment. Nature communications, 15(1), 2057.

  • Vaidya, H., Desell, T., Mali, A., & Ororbia, A. (2024). Neuro-mimetic Task-free Unsupervised Online Learning with Continual Self-Organizing Maps. arXiv preprint arXiv:2402.12465.

  • Ororbia, A., Mali, A., Kohan, A., Millidge, B., & Salvatori, T. (2024). A review of neuroscience-inspired machine learning. arXiv preprint arXiv:2403.18929.

  • Fernandez, A., & Mali, A. (2024). Stable and Robust Deep Learning By Hyperbolic Tangent Exponential Linear Unit (TeLU). arXiv preprint arXiv:2402.02790.

  • Dave, N., Kifer, D., Giles, C. L., & Mali, A. (2024). Stability Analysis of Various Symbolic Rule Extraction Methods from Recurrent Neural Network. arXiv preprint arXiv:2402.02627.

  • Stogin, J., Mali, A., & Giles, C. L. (2024). A provably stable neural network Turing Machine with finite precision and time. Information Sciences, 658, 120034.

2023

  • Bi, A., Velaga, T., Yu, J., Yu, P., Mali, A., Shokouhi, P., ... & Marone, C. (2023). Machine Learning to Connect Permeability Evolution to Microearthquakes in Hydraulic Stimulations for Enhanced Geothermal Systems. AGU23.

  • Zee, T., Ororbia, A. G., Mali, A., & Nwogu, I. (2022). A robust backpropagation-free framework for images. arXiv preprint arXiv:2206.01820.

  • Mali, A., Ororbia, A., Kifer, D., & Giles, L. (2023). On the computational complexity and formal hierarchy of second order recurrent neural networks. arXiv preprint arXiv:2309.14691.

  • Salvatori, T., Mali, A., Buckley, C. L., Lukasiewicz, T., Rao, R. P., Friston, K., & Ororbia, A. (2023). Brain-inspired computational intelligence via predictive coding. arXiv preprint arXiv:2308.07870.

  • Ororbia, A. G., Mali, A., Kifer, D., & Giles, C. L. (2023, June). Backpropagation-free deep learning with recursive local representation alignment. In Proceedings of the AAAI conference on artificial intelligence (Vol. 37, No. 8, pp. 9327-9335).

  • Borate, P., Rivière, J., Marone, C., Mali, A., Kifer, D., & Shokouhi, P. (2023). Using a physics-informed neural network and fault zone acoustic monitoring to predict lab earthquakes. Nature communications, 14(1), 3693.

  • Ororbia, A., & Mali, A. (2023, May). Active predictive coding: Brain-inspired reinforcement learning for sparse reward robotic control problems. In 2023 IEEE International Conference on Robotics and Automation (ICRA) (pp. 3015-3021). IEEE.

  • Shokouhi, P., Borate, P., Riviere, J., Mali, A., & Kifer, D. (2023, May). Physics-guided machine learning for laboratory earthquake prediction. In EGU General Assembly Conference Abstracts (pp. EGU-15437).

  • Ororbia, A., & Mali, A. (2023). The predictive forward-forward algorithm. arXiv preprint arXiv:2301.01452.

2022

  • Borate, P., Riviere, J., Marone, C., Mali, A., Kifer, D., & Shokouhi, P. (2022, December). A Physics-informed Machine Learning (PIML) Model for Lab Earthquake Prediction using Time-lapse Active Source Ultrasonic Data. In AGU Fall Meeting Abstracts (Vol. 2022, pp. S55A-08).

  • Ororbia, A., & Mali, A. (2022). Convolutional neural generative coding: Scaling predictive coding to natural images. arXiv preprint arXiv:2211.12047.

  • Ororbia, A., & Mali, A. (2022). Backprop-free reinforcement learning with active neural generative coding. In Proceedings of the AAAI Conference on Artificial Intelligence (pp. 29–37).

  • Nguyen, K. N., Tang, Z., Mali, A., & Kelly, A. (2022). Like a bilingual baby: The advantage of visually grounding a bilingual language model. arXiv preprint arXiv:2210.05487.

  • Ororbia, A. G., & Mali, A. (2022, June). Backprop-free reinforcement learning with active neural generative coding. In Proceedings of the AAAI Conference on Artificial Intelligence (Vol. 36, No. 1, pp. 29-37).

  • Mali, A., Ororbia, A., Kifer, D., & Giles, C. (2022). Neural JPEG: End-to-End Image Compression Leveraging a Standard JPEG Encoder-Decoder. In 2022 Data Compression Conference (DCC) (pp. 471-471).

  • Mali, A. A. (2022). Theoretically deriving computational limits of Artificial Neural Networks with bounded precision and time (Doctoral dissertation, Pennsylvania State University).

2021

  • Mali, A., Ororbia, A., Kifer, D., & Giles, L. (2021). Recognizing Long Grammatical Sequences using Recurrent Networks Augmented with an External Differentiable Stack. In Proceedings of the Fifteenth International Conference on Grammatical Inference (pp. 130–153). PMLR.

  • Ankur Mali, Alexander Ororbia, Daniel Kifer, & C. L. Giles (2021). An Empirical Analysis of Recurrent Learning Algorithms in Neural Lossy Image Compression Systems. 2021 Data Compression Conference (DCC), 356-356.

  • Mali, A., Ororbia, A., Kifer, D., & Giles, L. (2021). Investigating Backpropagation Alternatives when Learning to Dynamically Count with Recurrent Neural Networks. In Proceedings of the Fifteenth International Conference on Grammatical Inference (pp. 154–175). PMLR.

  • Rao, S., Kumar, V., Kifer, D., Giles, C., & Mali, A. (2021). OmniLayout: Room Layout Reconstruction From Indoor Spherical Panoramas. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops (pp. 3706-3715).

  • Ankur Arjun Mali, Alexander G. Ororbia II, Daniel Kifer, & C. Lee Giles (2021). Recognizing and Verifying Mathematical Equations using Multiplicative Differential Neural Units. In Thirty-Fifth AAAI Conference on Artificial Intelligence, AAAI 2021, Thirty-Third Conference on Innovative Applications of Artificial Intelligence, IAAI 2021, The Eleventh Symposium on Educational Advances in Artificial Intelligence, EAAI 2021, Virtual Event, February 2-9, 2021 (pp. 5006–5015). AAAI Press.

  • Ankur Arjun Mali, Alexander G. Ororbia II, & C. Lee Giles (2021). A Neural State Pushdown Automata. IEEE Trans. Artif. Intell., 1(3), 193–205.

2020 - 2013

  • Gopalakrishnan, A., Mali, A., Kifer, D., Giles, L., & Ororbia, A. G. (2019). A neural temporal model for human motion prediction. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (pp. 12116-12125).

  • A. Ororbia, A. Mali, C. L. Giles, & D. Kifer (2020). Continual Learning of Recurrent Neural Networks by Locally Aligning Distributed Representations. IEEE Transactions on Neural Networks and Learning Systems, 1-12.

  • Sudeep D. Thepade, Krishnasagar Subhedarpage, Ankur Mali*, & Tushar S. Vaidya (2013). Performance Gain of Content Based Video Retrieval Technique using Intermediate Block Truncation Coding on Different Color Spaces. 2013 International Conference on Communication and Signal Processing, 1017-1020.

  • Thepade, S., Subhedarpage, K., Mali*, ., & Vaidya, T. (2013). Performance Augmentation of Video Retrieval using Even-Odd Videos with Multilevel Block Truncation Coding. International Journal of Computer Applications, 64(9).

  • Thepade, S., Mali, ., & Subhedarpage*, K. (2014). Content Based Video Retrieval using Thepade’s Ternary Block Truncation Coding and Thepade’s Sorted Ternary Block Truncation Coding with Various Color Spaces. International Journal of Emerging Technologies in Computational and Applied Sciences, 8(6), 462–466.

  • A. Gopalakrishnan, A. Mali, D. Kifer, L. Giles, & A. G. Ororbia (2019). A Neural Temporal Model for Human Motion Prediction. In 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) (pp. 12108-12117).

  • Ororbia, A., Mali, A., Kelly, M., & Reitter, D. (2019). Like a Baby: Visually Situated Neural Language Acquisition. In Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics (pp. 5127–5136).

  • Alexander G. Ororbia II, & Ankur Mali (2019). Biologically Motivated Algorithms for Propagating Local Target Representations. In The Thirty-Third AAAI Conference on Artificial Intelligence, AAAI 2019, The Thirty-First Innovative Applications of Artificial Intelligence Conference, IAAI 2019, The Ninth AAAI Symposium on Educational Advances in Artificial Intelligence, EAAI 2019, Honolulu, Hawaii, USA, January 27 - February 1, 2019 (pp. 4651–4658). AAAI Press.

  • A. G. Ororbia, A. Mali, J. Wu, S. O’Connell, W. Dreese, D. Miller, & C. L. Giles (2019). Learned Neural Iterative Decoding for Lossy Image Compression Systems. In 2019 Data Compression Conference (DCC) (pp. 3-12).

  • Thepade, S., Subhedarpage, K., Mali*, ., & Vaidya, T. (2013). Color Content Based Video Retrieval using Block Truncation Coding with Different Color Spaces. International Journal of Computer Applications, 64(3).

  • Thepade, S., Subhedarpage, K., & Mali, . (2013). Performance Rise in Content Based Video Retrieval using Multi-level Thepade’s Sorted Ternary Block Truncation Coding with intermediate block videos and even-odd videos. In Advances in Computing, Communications and Informatics , 2013 International Conference on (pp. 962–966).

  • A. Mali, A. G. Ororbia, & C. L. Giles (2020). The Sibling Neural Estimator: Improving Iterative Image Decoding with Gradient Communication. In 2020 Data Compression Conference (DCC) (pp. 23-32).