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[1] Yu Wang,et al. MErging the Interface: Power, area and accuracy co-optimization for RRAM crossbar-based mixed-signal computing system , 2015, 2015 52nd ACM/EDAC/IEEE Design Automation Conference (DAC).
[2] Emmanuelle J. Merced-Grafals,et al. Repeatable, accurate, and high speed multi-level programming of memristor 1T1R arrays for power efficient analog computing applications , 2016, Nanotechnology.
[3] Tara N. Sainath,et al. FUNDAMENTAL TECHNOLOGIES IN MODERN SPEECH RECOGNITION Digital Object Identifier 10.1109/MSP.2012.2205597 , 2012 .
[4] Chih-Cheng Chang,et al. Mitigating Asymmetric Nonlinear Weight Update Effects in Hardware Neural Network Based on Analog Resistive Synapse , 2018, IEEE Journal on Emerging and Selected Topics in Circuits and Systems.
[5] Jian Sun,et al. Deep Residual Learning for Image Recognition , 2015, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[6] Fu Jie Huang,et al. A Tutorial on Energy-Based Learning , 2006 .
[7] Sangsu Park,et al. Conductive-bridging random-access memories for emerging neuromorphic computing. , 2020, Nanoscale.
[8] Qing Wu,et al. Efficient and self-adaptive in-situ learning in multilayer memristor neural networks , 2018, Nature Communications.
[9] F. Merrikh Bayat,et al. Fast, energy-efficient, robust, and reproducible mixed-signal neuromorphic classifier based on embedded NOR flash memory technology , 2017, 2017 IEEE International Electron Devices Meeting (IEDM).
[10] Yoshua Bengio,et al. Equilibrium Propagation with Continual Weight Updates , 2019, ArXiv.
[11] James C. R. Whittington,et al. Theories of Error Back-Propagation in the Brain , 2019, Trends in Cognitive Sciences.
[12] Lukasz Kaiser,et al. Attention is All you Need , 2017, NIPS.
[13] Advait Madhavan,et al. Streaming Batch Eigenupdates for Hardware Neural Networks , 2019, Front. Neurosci..
[14] Peng Lin,et al. Reinforcement learning with analogue memristor arrays , 2019, Nature Electronics.
[15] Paolo Fantini,et al. Unsupervised Learning by Spike Timing Dependent Plasticity in Phase Change Memory (PCM) Synapses , 2016, Front. Neurosci..
[16] Yoshua Bengio,et al. Updates of Equilibrium Prop Match Gradients of Backprop Through Time in an RNN with Static Input , 2019, NeurIPS.
[17] Yoshua Bengio,et al. Understanding the difficulty of training deep feedforward neural networks , 2010, AISTATS.
[18] Armantas Melianas,et al. Parallel programming of an ionic floating-gate memory array for scalable neuromorphic computing , 2019, Science.
[19] Jacques-Olivier Klein,et al. Spin-Transfer Torque Magnetic Memory as a Stochastic Memristive Synapse for Neuromorphic Systems , 2015, IEEE Transactions on Biomedical Circuits and Systems.
[20] Catherine Graves,et al. Dot-product engine for neuromorphic computing: Programming 1T1M crossbar to accelerate matrix-vector multiplication , 2016, 2016 53nd ACM/EDAC/IEEE Design Automation Conference (DAC).
[21] Ahmed Faraz Khan. Bidirectional Learning in Recurrent Neural Networks Using Equilibrium Propagation , 2018 .
[22] Yoshua Bengio,et al. Equilibrium Propagation: Bridging the Gap between Energy-Based Models and Backpropagation , 2016, Front. Comput. Neurosci..
[23] Yoshua Bengio,et al. Generalization of Equilibrium Propagation to Vector Field Dynamics , 2018, ArXiv.
[24] J J Hopfield,et al. Neural networks and physical systems with emergent collective computational abilities. , 1982, Proceedings of the National Academy of Sciences of the United States of America.
[25] Pritish Narayanan,et al. Neuromorphic computing using non-volatile memory , 2017 .
[26] J. Yang,et al. Memristive crossbar arrays for brain-inspired computing , 2019, Nature Materials.
[27] William J. Dally,et al. Analog/Mixed-Signal Hardware Error Modeling for Deep Learning Inference , 2019, 2019 56th ACM/IEEE Design Automation Conference (DAC).
[28] Pritish Narayanan,et al. Equivalent-accuracy accelerated neural-network training using analogue memory , 2018, Nature.
[29] Shimeng Yu,et al. Ferroelectric FET analog synapse for acceleration of deep neural network training , 2017, 2017 IEEE International Electron Devices Meeting (IEDM).
[30] Yoshua Bengio,et al. Generative Adversarial Nets , 2014, NIPS.
[31] Max Welling,et al. Initialized Equilibrium Propagation for Backprop-Free Training , 2019, ICLR.
[32] Fernando Corinto,et al. Equilibrium Propagation for Memristor-Based Recurrent Neural Networks , 2020, Frontiers in Neuroscience.
[33] Stephen Grossberg,et al. Absolute stability of global pattern formation and parallel memory storage by competitive neural networks , 1983, IEEE Transactions on Systems, Man, and Cybernetics.
[34] Javier R. Movellan,et al. Contrastive Hebbian Learning in the Continuous Hopfield Model , 1991 .
[35] Wei Yang Lu,et al. Nanoscale memristor device as synapse in neuromorphic systems. , 2010, Nano letters.
[36] L. Chua. Memristor-The missing circuit element , 1971 .
[37] J J Hopfield,et al. Neurons with graded response have collective computational properties like those of two-state neurons. , 1984, Proceedings of the National Academy of Sciences of the United States of America.
[38] Carver Mead,et al. Analog VLSI and neural systems , 1989 .
[39] Geoffrey E. Hinton,et al. A Learning Algorithm for Boltzmann Machines , 1985, Cogn. Sci..
[40] Brendan Fong,et al. A Compositional Framework for Passive Linear Networks , 2015, 1504.05625.
[41] Surya Ganguli,et al. A deep learning framework for neuroscience , 2019, Nature Neuroscience.
[42] Yoshua Bengio,et al. Equivalence of Equilibrium Propagation and Recurrent Backpropagation , 2017, Neural Computation.
[43] Yoshua Bengio,et al. Gradient-based learning applied to document recognition , 1998, Proc. IEEE.
[44] Juan C. Nino,et al. Deep Learning in Memristive Nanowire Networks , 2020, ArXiv.
[45] Sujan Kumar Gonugondla,et al. An MRAM-Based Deep In-Memory Architecture for Deep Neural Networks , 2019, 2019 IEEE International Symposium on Circuits and Systems (ISCAS).
[46] Adam Santoro,et al. Backpropagation and the brain , 2020, Nature Reviews Neuroscience.
[47] Heiga Zen,et al. WaveNet: A Generative Model for Raw Audio , 2016, SSW.
[48] Yachen Xiang,et al. Hardware implementation of RRAM based binarized neural networks , 2019, APL Materials.
[49] Max Welling,et al. Training a Spiking Neural Network with Equilibrium Propagation , 2019, AISTATS.
[50] Kari Christianson,et al. Nonlinear Electrical Networks , 2010 .