- C-LSTM: Enabling Efficient LSTM using Structured Compression Techniques on FPGAs
- Sparse deep predictive coding captures contour integration capabilities of the early visual system
- CHIPKIT: An agile, reusable open-source framework for rapid test chip development
- A Deep Learning Framework for Simulation and Defect Prediction Applied in Microelectronics
- A Survey of Deep Learning for Scientific Discovery
- Closing the Analog Design Loop with the Berkeley Analog Generator
- IncPIRD: Fast Learning-Based Prediction of Incremental IR Drop
- A Deep Reinforcement Learning Approach for Global Routing
- Learning to Navigate in CitiesWithout a Map
- Attention Routing: track-assignment detailed routing using attention-based reinforcement learning
- Neural Speech Synthesis with Transformer Network
- Cross-layer Optimization for High Speed Adders: A Pareto Driven Machine Learning Approach
- Low Power Design Automation
- DREAMPlace 3.0: Multi-Electrostatics Based Robust VLSI Placement with Region Constraints
- Painting on Placement: Forecasting Routing Congestion using Conditional Generative Adversarial Nets
- BagNet: Berkeley Analog Generator with Layout Optimizer Boosted with Deep Neural Networks
- AutoPhase: Juggling HLS Phase Orderings in Random Forests with Deep Reinforcement Learning
- End-to-end deep reinforcement learning in computer systems
- GAN-CTS: A Generative Adversarial Framework for Clock Tree Prediction and Optimization
- A View on Deep Reinforcement Learning in System Optimization
- Extending High-Level Synthesis for Task-Parallel Programs
- GCN-RL Circuit Designer: Transferable Transistor Sizing with Graph Neural Networks and Reinforcement Learning
- GeniusRoute: A New Analog Routing Paradigm Using Generative Neural Network Guidance
- Chip Placement with Deep Reinforcement Learning
- Blockchain-enabled Data Collection and Sharing for Industrial IoT with Deep Reinforcement Learning
- Machine learning enables completely automatic tuning of a quantum device faster than human experts
- Neural Systems for Control
- Performance Estimation of Synthesis Flows cross Technologies using LSTMs and Transfer Learning
- Deep Learning-Driven Simultaneous Layout Decomposition and Mask Optimization
- PRIMAL: Power Inference using Machine Learning
- Improving predictive mapping of deep-water habitats: Considering multiple model outputs and ensemble techniques
- High Performance Graph Convolutional Networks with Applications in Testability Analysis
- RouteNet: Routability Prediction for Mixed-Size Designs Using Convolutional Neural Network
- PowerPlanningDL: Reliability-Aware Framework for On-Chip Power Grid Design using Deep Learning
- Residual Learning of Video Frame Interpolation Using Convolutional LSTM
- Learning to Design Circuits
- OpenROAD: Toward a Self-Driving, Open-Source Digital Layout Implementation Tool Chain
- Learning-Based CPU Power Modeling
- Building high accuracy emulators for scientific simulations with deep neural architecture search
- Placement Optimization with Deep Reinforcement Learning
- Understanding Graphs in EDA: From Shallow to Deep Learning
- AutoCkt: Deep Reinforcement Learning of Analog Circuit Designs
- An Imitation Learning Approach for Cache Replacement
- MAGICAL: Toward Fully Automated Analog IC Layout Leveraging Human and Machine Intelligence
- GANVO: Unsupervised Deep Monocular Visual Odometry and Depth Estimation with Generative Adversarial Networks
- Approximate Logic Synthesis: A Reinforcement Learning-Based Technology Mapping Approach
- Cyber-secure decentralized energy management for IoT-enabled active distribution networks
- Challenges and opportunities toward fully automated analog layout design
- RTL to Transistor Level Power Modelling and Estimation Techniques for FPGA and ASIC: A Survey
- A Multidisciplinary Approach for the Development of Smart Distribution Networks
- Template-based PDN Synthesis in Floorplan and Placement Using Classifier and CNN Techniques
- AutoPhase: Compiler Phase-Ordering for High-Level Synthesis with Deep Reinforcement Learning
- Dual Motion GAN for Future-Flow Embedded Video Prediction
- Towards Decrypting the Art of Analog Layout: Placement Quality Prediction via Transfer Learning
- An Agent-Training Framework for Coping with Environments with Slow Simulators that have Fast Approximations
- Solving Packing Problems by Conditional Query Learning
- New Full Adders Using Multi-Layer Perceptron Network
- A Learning Bridge from Architectural Synthesis to Physical Design for Exploring Power Efficient High-Performance Adders
- The Deep Learning Revolution and Its Implications for Computer Architecture and Chip Design
- Park: An Open Platform for Learning-Augmented Computer Systems
- How Deep Learning Can Drive Physical Synthesis Towards More Predictable Legalization
- Deep Learning-Based Circuit Recognition Using Sparse Mapping and Level-Dependent Decaying Sum Circuit Representations
- Deep Analog-to-Digital Converter for Wireless Communication
- Adaptive Layout Decomposition with Graph Embedding Neural Networks
- Exploring a Machine Learning Approach to Performance Driven Analog IC Placement
- Generalized Clustering by Learning to Optimize Expected Normalized Cuts
- A Parallel GPU Implementation of the TimberWolf Placement Algorithm
- Long Short Term Based Memory Hardware Prefetcher
- A Data-Driven Frequency Scaling Approach for Deadline-aware Energy Efficient Scheduling on Graphics Processing Units (GPUs)
- An Extensive Study on Cross-project Predictive Mutation Testing
- High-Definition Routing Congestion Prediction for Large-Scale FPGAs
- Late Breaking Results: Analog Circuit Generator based on Deep Neural Network enhanced Combinatorial Optimization
- Reinforcement Learning Driven Heuristic Optimization
- Generalized Clustering by Learning to Optimize Expected Normalized Cuts
- MC3: A Cloud Caching Strategy for Next Generation Virtual Content Distribution Networks
- Deep-PowerX: A Deep Learning-Based Framework for Low-Power Approximate Logic Synthesis
- Deep Learning Inversion of Electrical Resistivity Data
- Learning To Route
- Can Q-Learning with Graph Networks Learn a Generalizable Branching Heuristic for a SAT Solver?
- Analog Circuit Design with Dyna-Style Reinforcement Learning
- Unidirectional long short-term memory recurrent neural network with recurrent output layer for low-latency speech synthesis
- Routability-Driven Macro Placement with Embedded CNN-Based Prediction Model
- Online Adaptive Learning for Runtime Resource Management of Heterogeneous SoCs
- CSM-NN: Current Source Model Based Logic Circuit Simulation - A Neural Network Approach
- Circuit Routing Using Monte Carlo Tree Search and Deep Neural Networks
- Global Placement with Deep Learning-Enabled Explicit Routability Optimization
- A Survey of Machine Learning Applied to Computer Architecture Design
- A deep learning framework for graph partitioning
- IR-aware Power Net Routing for Multi-Voltage Mixed-Signal Design
- Electric Analog Circuit Design with Hypernetworks and a Differential Simulator
- NN-PARS: A Parallelized Neural Network Based Circuit Simulation Framework
- Fast Design Space Adaptation with Deep Reinforcement Learning for Analog Circuit Sizing
- A Survey of Adaptive Compiler Optimization Heuristics
- Towards traffic matrix prediction with LSTM recurrent neural networks
- DREAMPlace 2.0: Open-Source GPU-Accelerated Global and Detailed Placement for Large-Scale VLSI Designs
- Machine Learning Based Fast Power Integrity Classifier
- A Survey of Machine Learning and Deep Learning Techniques for Compiler Optimization
- Understanding Memory Access Patterns for Prefetching
- Reinforcement learning applications
- Inception loops discover what excites neurons most using deep predictive models
- Network System Optimization with Reinforcement Learning: Methods and Applications
- Deep Predictive Coding for Spatiotemporal Representation Learning
- New Applications of Learning-Based Modeling in Nanoscale Integrated-Circuit Design
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