1,686 technical terms and definitions
Deep Learning for Individual Treatment Effect Estimation (Extended Study) Introduction & Motivation Deep Learning for Individual Treatment Effect Estimation (Extended Study)…
Deep Learning Architectures for Forecasting Introduction & Motivation Deep Learning Architectures for Forecasting addresses a central problem in timeseries forecasting…
deep learning neural network yield prediction prediction, deep learning neural, learning neural network, neural network yield, network yield prediction
Deep Learning Neural Network Yield Prediction Prediction with Machine Learning Introduction & Motivation Deep Learning Neural Network Yield Prediction Prediction with Machine…
Deep Learning: Neural Network Architectures, Backpropagation, and Optimization Deep learning extends classical neural networks with multiple layers of learned representations…
loss surface neural network, saddle point optimization, sharpness aware minimization, loss landscape geometry
Deep Learning Optimization Landscape is the geometric study of the loss function surface in neural network parameter space — where understanding the structure of minima (sharp vs.…
deep learning recommendation embedding prediction, deep learning recommendation, learning recommendation embedding, recommendation embedding prediction, deep learning
Deep Learning Recommendation Embedding Prediction with Machine Learning Introduction & Motivation Deep Learning Recommendation Embedding Prediction with Machine Learning addresses…
Deep Learning for Recommender Systems Introduction & Motivation Deep Learning for Recommender Systems addresses a central problem in recsys systems and {target} optimization: how…
temporal fusion transformer, time series forecasting deep learning, sequence prediction temporal, transformer time series
Deep learning is the subfield of machine learning that uses neural networks with many layers (deep architectures) to learn hierarchical representations of data — automatically…
deep learning time series, deep learning time, learning time series, deep learning, learning time, time series
Deep Learning Time Series Introduction & Motivation Deep Learning Time Series addresses a central problem in timeseries process control and deep-architecture-multilayer-learning…
deep level transient spectroscopy drift prediction machine learning, deep level, transient spectroscopy drift, dlts, deep level transient, level transient
Deep Level Transient Spectroscopy Drift Prediction with Machine Learning Introduction & Motivation Deep Level Transient Spectroscopy Drift Prediction with Machine Learning…
deep-level transient spectroscopy trap signature prediction, deep-level transient spectroscopy, transient spectroscopy trap, spectroscopy trap signature
Deep-Level Transient Spectroscopy Trap Signature Prediction with Machine Learning Introduction & Motivation Deep-Level Transient Spectroscopy Trap Signature Prediction…
deep metric learning triplet optimization prediction, deep metric learning, metric learning triplet, learning triplet optimization, triplet optimization prediction
Deep Metric Learning Triplet Optimization Prediction with Machine Learning Introduction & Motivation Deep Metric Learning Triplet Optimization Prediction with Machine Learning…
deep n-well, dnw, process
Deep N-well (DNW) is a buried, high-energy-implanted N-type layer that forms the floor of a triple-well tub, electrically isolating a P-well "island" from the P-substrate beneath…
deep pipeline and branch misprediction penalty scaling, deep pipeline branch, pipeline branch misprediction, branch misprediction penalty, misprediction penalty scaling
Deep Pipeline and Branch Misprediction Penalty Scaling Introduction & Motivation Deep Pipeline and Branch Misprediction Penalty Scaling addresses a central problem in cpu-arch…
deep q learning dqn, deep learning dqn, deep learning, learning dqn
Deep Q Learning DQN Introduction & Motivation Deep Q Learning DQN addresses a central problem in robotics process control and deep-neural-network-q-value prediction: how…
experience replay dqn, target network dqn, double dqn dueling network, atari reinforcement learning
Deep Q-Network (DQN) is the foundational deep reinforcement learning algorithm approximating Q-values with neural networks — introducing experience replay and target networks…
Deep Q-Network Architecture Introduction & Motivation Deep Q-Network Architecture addresses a central problem in reinforcement policy learning and dqn-stability-improvement…
Deep Q-Networks (DQN) Introduction & Motivation Deep Q-Networks (DQN) addresses a central problem in sequential decision making via deeprl: how to Learn a policy that maximizes…
Deep Q-Networks (DQN) (Extended Study) Introduction & Motivation Deep Q-Networks (DQN) (Extended Study) addresses a central problem in sequential decision making via deeprl: how…
Deep Q-Networks (DQN) (Extended Study) Introduction & Motivation Deep Q-Networks (DQN) (Extended Study) addresses a central problem in sequential decision making via deeprl: how…
Deep Q-Networks (DQN) (Extended Study) Introduction & Motivation Deep Q-Networks (DQN) (Extended Study) addresses a central problem in sequential decision making via deeprl: how…
Monotonic Deep Quantile Regression Networks Introduction & Motivation Monotonic Deep Quantile Regression Networks addresses a central problem in uncertainty methods and prediction…
The Bosch Process: Where Scallops Actually Come From Keyword focus: deep reactive ion etching DRIE Bosch process passivation C4F8 etch SF6 scalloping high aspect ratio silicon HAR…
drie, advanced packaging, bosch process, tsv etch
Through-Silicon Vias are the vertical conductive interconnect pillars that traverse the bulk silicon substrate to establish high-density, low-latency electrical connections…
Deep Reinforcement Learning 1. Introduction to Deep Reinforcement Learning Deep Reinforcement Learning (Deep RL) extends classical RL by using deep neural networks to approximate…
sim to real transfer, domain randomization robot, drl robot manipulation, reinforcement learning locomotion
Deep Reinforcement Learning (DRL) for Robotics is the application of neural network-based reinforcement learning agents to robotic control tasks including manipulation…
deep rie sidewall angle prediction machine learning, deep rie, sidewall angle prediction, rf rie, deep rie sidewall angle prediction, deep rie sidewall, rie sidewall angle
Deep RIE Sidewall Angle Prediction with Machine Learning Introduction & Motivation Deep RIE Sidewall Angle Prediction with Machine Learning addresses a central problem in deep…
Deep SHAP DeepLIFT Additive Attributions Introduction & Motivation Deep SHAP DeepLIFT Additive Attributions addresses a central problem in explainability interpretation and model…
deep silicon etch undercut control prediction, deep silicon etch, silicon etch undercut, etch undercut control, undercut control prediction, deep silicon, silicon etch
Deep Silicon Etch Undercut Control Prediction with Machine Learning Introduction & Motivation Deep Silicon Etch Undercut Control Prediction with Machine Learning addresses…
deep space electronics thermal cycling prediction, deep space electronics, space electronics thermal, electronics thermal cycling, thermal cycling prediction, deep space
Deep Space Electronics Thermal Cycling Prediction with Machine Learning Introduction & Motivation Deep Space Electronics Thermal Cycling Prediction with Machine Learning addresses…
deep submicron cmos scaling 1990s step 12 adopt chemical mechanical polishing for planarization, adopt chemical mechanical polishing for planarization
Deep Submicron CMOS Scaling (1990s): Step 12 — Adopt Chemical-Mechanical Polishing for Multilevel Planarization 1. Why Flat Matters More as Layers Stack Up A single metal…
deep submicron cmos scaling 1990s step 17 assemble the 0.25 micron node baseline, assemble the 0.25 micron node baseline
Deep Submicron CMOS Scaling (1990s): Step 17 — Assemble the 0.25-Micron Node as the Deep Submicron Baseline 1. Bringing the Series' Separate Fixes Together Into One Process Each…
deep submicron cmos scaling 1990s step 20 close the series and mark the boundary with the next era, close the series and mark the boundary with the next era
Deep Submicron CMOS Scaling (1990s): Step 20 — Close the Series and Mark the Boundary With the Next Scaling Era 1. What This Series Has Established Across twenty steps, this…
deep submicron cmos scaling 1990s step 10 confront interconnect rc delay as a design concern, confront interconnect rc delay as a design concern
Deep Submicron CMOS Scaling (1990s): Step 10 — Confront Interconnect RC Delay as a First-Order Design Concern 1. A Reversal From the 1980s Design Picture Through the 1980s, gate…
deep submicron cmos scaling 1990s step 1 confront the new scaling wall below one micron, confront the new scaling wall below one micron
Deep Submicron CMOS Scaling (1990s): Step 1 — Confront the New Scaling Wall Below One Micron 1. The Geometric Shrink Alone Stops Being Enough Through the 1980s…
deep submicron cmos scaling 1990s step 14 engineer halo pocket implants for threshold rolloff control, engineer halo pocket implants for threshold rolloff control
Deep Submicron CMOS Scaling (1990s): Step 14 — Engineer Halo/Pocket Implants for Threshold-Voltage Rolloff Control 1. A Short-Channel Effect That Deep Submicron Geometries…
deep submicron cmos scaling 1990s step 3 engineer the lightly doped drain structure, engineer the lightly doped drain structure
Deep Submicron CMOS Scaling (1990s): Step 3 — Engineer the Lightly Doped Drain (LDD) Structure 1. The Core Idea: Grade the Field Instead of Fighting It Directly A conventional…
deep submicron cmos scaling 1990s step 2 identify hot carrier injection as the new reliability limit, identify hot carrier injection as the new reliability limit
Deep Submicron CMOS Scaling (1990s): Step 2 — Identify Hot-Carrier Injection as the New Reliability Limit 1. A Mechanism the 1970s Series Already Named, Now the Dominant Concern…
deep submicron cmos scaling 1990s step 4 integrate sidewall spacers for self aligned ldd implants, integrate sidewall spacers for self aligned ldd implants
Deep Submicron CMOS Scaling (1990s): Step 4 — Integrate Sidewall Spacers for Self-Aligned LDD Implants 1. The Alignment Problem LDD Creates Step 3 described two differently doped…
deep submicron cmos scaling 1990s step 8 integrate the self aligned salicide process, integrate the self aligned salicide process
Deep Submicron CMOS Scaling (1990s): Step 8 — Integrate the Self-Aligned Salicide (SALICIDE) Process 1. Siliciding the Gate and the Diffusions Without Extra Masks Step 7…
deep submicron cmos scaling 1990s step 18 quantify what the 0.25 micron baseline delivered, quantify what the 0.25 micron baseline delivered
Deep Submicron CMOS Scaling (1990s): Step 18 — Quantify What the 0.25-Micron Baseline Delivered Over the Decade 1. From a One-Micron Starting Point to a Quarter-Micron Close This…
deep submicron cmos scaling 1990s step 16 rebalance threshold voltage against a scaled supply rail, rebalance threshold voltage against a scaled supply rail
Deep Submicron CMOS Scaling (1990s): Step 16 — Rebalance Threshold Voltage Against a Scaled Supply Rail 1. Why Threshold Voltage Cannot Simply Stay Fixed as Supply Falls…
deep submicron cmos scaling 1990s step 7 reduce sheet resistance with silicide, reduce sheet resistance with silicide
Deep Submicron CMOS Scaling (1990s): Step 7 — Reduce Polysilicon and Diffusion Sheet Resistance With Silicide 1. A Resistance Problem That Scaling Makes Worse, Not Better…
deep submicron cmos scaling 1990s step 13 replace locos with shallow trench isolation, replace locos with shallow trench isolation
Deep Submicron CMOS Scaling (1990s): Step 13 — Replace LOCOS With Shallow Trench Isolation 1. Why LOCOS Ran Out of Room The `mosfet_scaling_1970s` series' step 7 established LOCOS…
deep submicron cmos scaling 1990s step 9 scale multilevel interconnect and adopt tungsten plugs, scale multilevel interconnect and adopt tungsten plugs
Deep Submicron CMOS Scaling (1990s): Step 9 — Scale Multilevel Interconnect and Adopt Tungsten Plugs 1. More Metal Layers, a Harder Via Problem As logic density grew through deep…
deep submicron cmos scaling 1990s step 15 scale supply voltage from five volts toward lower rails, scale supply voltage from five volts toward lower rails
Deep Submicron CMOS Scaling (1990s): Step 15 — Scale Supply Voltage From Five Volts Toward 3.3 Volts and Below 1. Why 5V Persisted Longer Than Pure Scaling Theory Wanted Step 1…
deep submicron cmos scaling 1990s step 5 scale the gate oxide toward its tunneling limit, scale the gate oxide toward its tunneling limit
Deep Submicron CMOS Scaling (1990s): Step 5 — Scale the Gate Oxide Toward Its Tunneling Limit 1. Why the Oxide Has to Thin Along With Everything Else Gate oxide capacitance per…
deep submicron cmos scaling 1990s step 19 situate deep submicron cmos as foundation of the 1990s boom, situate deep submicron cmos as foundation of the 1990s boom
Deep Submicron CMOS Scaling (1990s): Step 19 — Situate Deep Submicron CMOS as the Foundation of the 1990s Microprocessor Boom 1. The Decade's Visible Story Rested on This Series'…
deep submicron cmos scaling 1990s step 6 weigh oxide thinning against reliability and leakage, weigh oxide thinning against reliability and leakage
Deep Submicron CMOS Scaling (1990s): Step 6 — Weigh Oxide Thinning Against Reliability and Leakage Tradeoffs 1. Combining Two Independent Field-Driven Risks Steps 2 through 4…
deep submicron cmos scaling 1990s step 11 weigh motivations for moving toward copper, weigh motivations for moving toward copper
Deep Submicron CMOS Scaling (1990s): Step 11 — Weigh the Motivations for Moving Beyond Aluminum Toward Copper 1. Aluminum's Two Compounding Weaknesses at Deep Submicron Dimensions…