2021.9.13 Neural papers

09-08-2021	RepNAS: Searching for Efficient Re-parameterizing Blocks by Mingyang Zhang et al
09-07-2021	Sparse Distributed Memory using Spiking Neural Networks on Nengo by Rohan Deepak Ajwani et al
09-09-2021	Deep Active Inference for Pixel-Based Discrete Control: Evaluation on the Car Racing Problem by Niels van Hoeffelen et al
09-08-2021	A robust approach for deep neural networks in presence of label noise: relabelling and filtering instances during training by Anabel Gómez-Ríos et al
09-07-2021	The Sensory Neuron as a Transformer: Permutation-Invariant Neural Networks for Reinforcement Learning by Yujin Tang et al
09-08-2021	Feature Selection on Thermal-stress Dataset by Xuyang Shen et al
09-09-2021	HSMD: An object motion detection algorithm using a Hybrid Spiking Neural Network Architecture by Pedro Machado et al
09-10-2021	ProcK: Machine Learning for Knowledge-Intensive Processes by Tobias Jacobs et al
09-08-2021	Resistive Neural Hardware Accelerators by Kamilya Smagulova et al
09-09-2021	Surrogate Parameters Optimization for Data and Model Fusion of COVID-19 Time-series Data by Timilehin Ogundare et al
09-08-2021	Quality-Diversity Meta-Evolution: customising behaviour spaces to a meta-objective by David M. Bossens et al
09-08-2021	Computing on Functions Using Randomized Vector Representations by E. Paxon Frady et al
09-08-2021	Cross-lingual Offensive Language Identification for Low Resource Languages: The Case of Marathi by Saurabh Gaikwad et al
09-09-2021	Characterization of Constrained Continuous Multiobjective Optimization Problems: A Feature Space Perspective by Aljoša Vodopija et al
09-09-2021	SONIC: A Sparse Neural Network Inference Accelerator with Silicon Photonics for Energy-Efficient Deep Learning by Febin Sunny et al
09-10-2021	Citizen centric optimal electric vehicle charging stations locations in a full city: case of Malaga by Christian Cintrano et al
09-09-2021	ErfAct: Non-monotonic smooth trainable Activation Functions by Koushik Biswas et al
09-07-2021	On the space of coefficients of a Feed Forward Neural Network by Dinesh Valluri et al