iVAMS 3.0: Hierarchical-Machine-Learning-Metamodel-Integrated Intelligent Verilog-AMS for Ultra-Fast, Accurate Mixed-Signal Design Optimization | Paper Citation Record

Observation bb7c3aab-02c1-4ad8-85b1-35411491c4ce · outbound

This paper cites Fast Design Optimization through Simple Kriging Metamodeling: A Sense Amplifier Case Study,.

iVAMS 3.0: Hierarchical-Machine-Learning-Metamodel-Integrated Intelligent Verilog-AMS for Ultra-Fast, Accurate Mixed-Signal Design Optimization Fast Design Optimization through Simple Kriging Metamodeling: A Sense Amplifier Case Study,

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:57:28.362377Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation d780f740-462a-496a-8e80-8f54c8d1f2b7 · outbound

This paper cites A Comparative Study of Metamodels for Fast and Accurate Simulation of Nano-CMOS Circuits,.

iVAMS 3.0: Hierarchical-Machine-Learning-Metamodel-Integrated Intelligent Verilog-AMS for Ultra-Fast, Accurate Mixed-Signal Design Optimization A Comparative Study of Metamodels for Fast and Accurate Simulation of Nano-CMOS Circuits,

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:57:28.342054Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation e792dd63-8658-4789-b0b8-cbc5e6a28562 · outbound

This paper cites A Comparative Study of Metamodels for Fast and Accurate Simulation of Nano-CMOS Circuits,.

iVAMS 3.0: Hierarchical-Machine-Learning-Metamodel-Integrated Intelligent Verilog-AMS for Ultra-Fast, Accurate Mixed-Signal Design Optimization A Comparative Study of Metamodels for Fast and Accurate Simulation of Nano-CMOS Circuits,

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:57:28.324867Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation bb9446ec-bd3e-4ce6-995c-5873d48e325f · outbound

This paper cites Towards Robust Nano-CMOS Sense Amplifier Design: A Dual-Threshold versus Dual-Oxide Perspective,.

iVAMS 3.0: Hierarchical-Machine-Learning-Metamodel-Integrated Intelligent Verilog-AMS for Ultra-Fast, Accurate Mixed-Signal Design Optimization Towards Robust Nano-CMOS Sense Amplifier Design: A Dual-Threshold versus Dual-Oxide Perspective,

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:57:28.304506Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 43134177-9694-4e9b-af53-ef4e167e636e · outbound

This paper cites Kriging Metamodeling in Discrete-Event Simulation: An Overview,.

iVAMS 3.0: Hierarchical-Machine-Learning-Metamodel-Integrated Intelligent Verilog-AMS for Ultra-Fast, Accurate Mixed-Signal Design Optimization Kriging Metamodeling in Discrete-Event Simulation: An Overview,

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:57:28.282357Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 41d36e59-da33-4b0b-99fe-459e8f966d50 · outbound

This paper cites Yield-Aware Analog Integrated Circuit Optimization Using Geostatistics Motivated Perfor- mance Modeling,.

iVAMS 3.0: Hierarchical-Machine-Learning-Metamodel-Integrated Intelligent Verilog-AMS for Ultra-Fast, Accurate Mixed-Signal Design Optimization Yield-Aware Analog Integrated Circuit Optimization Using Geostatistics Motivated Perfor- mance Modeling,

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:57:28.269112Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 15a700af-29c4-427f-b167-06cc21a0076a · outbound

This paper cites Kriging-Assisted Ultra-Fast Simulated-Annealing Optimization of a Clamped Bitline Sense Amplifier,.

iVAMS 3.0: Hierarchical-Machine-Learning-Metamodel-Integrated Intelligent Verilog-AMS for Ultra-Fast, Accurate Mixed-Signal Design Optimization Kriging-Assisted Ultra-Fast Simulated-Annealing Optimization of a Clamped Bitline Sense Amplifier,

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:57:28.255915Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 1822683f-e155-4538-a71f-643b817b127e · outbound

This paper cites Kriging Model Combined with Latin Hypercube Sampling for Surrogate Modeling of Analog Integrated Circuit Performance,.

iVAMS 3.0: Hierarchical-Machine-Learning-Metamodel-Integrated Intelligent Verilog-AMS for Ultra-Fast, Accurate Mixed-Signal Design Optimization Kriging Model Combined with Latin Hypercube Sampling for Surrogate Modeling of Analog Integrated Circuit Performance,

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:57:28.241858Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation c6c5683f-719c-477d-80b0-f06a100b7763 · outbound

This paper cites Advances in Particle Swarm Optimization for Antenna Designs: Real-Number, Bi- nary, Single-Objective and Multiobjective Implementations,.

iVAMS 3.0: Hierarchical-Machine-Learning-Metamodel-Integrated Intelligent Verilog-AMS for Ultra-Fast, Accurate Mixed-Signal Design Optimization Advances in Particle Swarm Optimization for Antenna Designs: Real-Number, Bi- nary, Single-Objective and Multiobjective Implementations,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:57:28.228332Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 98a0b946-5ab1-4952-b89e-9ff2e9b3bb00 · outbound

This paper cites Handling Multiple Objectives With Particle Swarm Opti- mization,.

iVAMS 3.0: Hierarchical-Machine-Learning-Metamodel-Integrated Intelligent Verilog-AMS for Ultra-Fast, Accurate Mixed-Signal Design Optimization Handling Multiple Objectives With Particle Swarm Opti- mization,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:57:28.214146Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 8714edbd-88d8-498a-b5bf-d4d3c6fc741c · outbound

This paper cites Using Particle Swarm Optimization in Training Neural Network for Indoor Field Strength Prediction,.

iVAMS 3.0: Hierarchical-Machine-Learning-Metamodel-Integrated Intelligent Verilog-AMS for Ultra-Fast, Accurate Mixed-Signal Design Optimization Using Particle Swarm Optimization in Training Neural Network for Indoor Field Strength Prediction,

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:57:28.199326Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation f94021e4-ca82-4943-91a9-378f1f5ac247 · outbound

This paper cites Fast Statistical Analysis of Process Variation Effects Using Accurate PLL Behavioral Models,.

iVAMS 3.0: Hierarchical-Machine-Learning-Metamodel-Integrated Intelligent Verilog-AMS for Ultra-Fast, Accurate Mixed-Signal Design Optimization Fast Statistical Analysis of Process Variation Effects Using Accurate PLL Behavioral Models,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:57:28.186018Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 48117448-95bf-4a9c-aeb9-b8c867ab43e4 · outbound

This paper cites [Online].

iVAMS 3.0: Hierarchical-Machine-Learning-Metamodel-Integrated Intelligent Verilog-AMS for Ultra-Fast, Accurate Mixed-Signal Design Optimization [Online]

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:57:28.172600Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 25c95185-03eb-40e4-ac17-b1d1fb5f335b · outbound

This paper cites Exploring Kriging for Fast and Accurate Design Optimization of Nanoscale Analog Circuits,.

iVAMS 3.0: Hierarchical-Machine-Learning-Metamodel-Integrated Intelligent Verilog-AMS for Ultra-Fast, Accurate Mixed-Signal Design Optimization Exploring Kriging for Fast and Accurate Design Optimization of Nanoscale Analog Circuits,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:57:28.159255Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 7c6199c4-3119-4421-934e-aed6bbaf900d · outbound

This paper cites Kriging Bootstrapped Neural Network Training for Fast and Accurate Process Variation Analysis,.

iVAMS 3.0: Hierarchical-Machine-Learning-Metamodel-Integrated Intelligent Verilog-AMS for Ultra-Fast, Accurate Mixed-Signal Design Optimization Kriging Bootstrapped Neural Network Training for Fast and Accurate Process Variation Analysis,

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:57:28.145664Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 7e3031fe-8c90-4cba-b643-0346ed95dddb · outbound

This paper cites Kriging Metamodeling in Multi-objective Simulation Optimization,.

iVAMS 3.0: Hierarchical-Machine-Learning-Metamodel-Integrated Intelligent Verilog-AMS for Ultra-Fast, Accurate Mixed-Signal Design Optimization Kriging Metamodeling in Multi-objective Simulation Optimization,

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:57:28.132397Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation dd9b1240-4b49-4526-8bba-7aebecf39752 · outbound

This paper cites Kriging Metamodeling in Con- strained Simulation Optimization: An Explorative Study,.

iVAMS 3.0: Hierarchical-Machine-Learning-Metamodel-Integrated Intelligent Verilog-AMS for Ultra-Fast, Accurate Mixed-Signal Design Optimization Kriging Metamodeling in Con- strained Simulation Optimization: An Explorative Study,

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:57:28.119094Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation b8295a69-d55b-4f1b-8162-6acd55e9a1ca · outbound

This paper cites Robust Simulation-Optimization using Metamodels,.

iVAMS 3.0: Hierarchical-Machine-Learning-Metamodel-Integrated Intelligent Verilog-AMS for Ultra-Fast, Accurate Mixed-Signal Design Optimization Robust Simulation-Optimization using Metamodels,

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:57:28.105876Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation cc867b7b-68ab-4e45-b495-4c2a1bddb027 · outbound

This paper cites Stochastic Kriging for Simulation Metamodeling,.

iVAMS 3.0: Hierarchical-Machine-Learning-Metamodel-Integrated Intelligent Verilog-AMS for Ultra-Fast, Accurate Mixed-Signal Design Optimization Stochastic Kriging for Simulation Metamodeling,

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:57:28.092477Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 4028a73d-1a4b-4e08-b5c0-71702a8f286c · outbound

This paper cites Analog Circuit Optimization using Evolutionary Algorithms and Convex Optimization,.

iVAMS 3.0: Hierarchical-Machine-Learning-Metamodel-Integrated Intelligent Verilog-AMS for Ultra-Fast, Accurate Mixed-Signal Design Optimization Analog Circuit Optimization using Evolutionary Algorithms and Convex Optimization,

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:57:28.078537Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 05251a9f-def4-4723-9be4-04bae2dedc73 · outbound

This paper cites A Hybrid Genetic Algorithm- Neural Network Strategy for Simulation Optimization,.

iVAMS 3.0: Hierarchical-Machine-Learning-Metamodel-Integrated Intelligent Verilog-AMS for Ultra-Fast, Accurate Mixed-Signal Design Optimization A Hybrid Genetic Algorithm- Neural Network Strategy for Simulation Optimization,

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:57:28.064405Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation c825436d-784e-4b23-8165-e9ee385d7ce8 · outbound

This paper cites Developing Optimal Neural Network Metamodels Based on Prediction Intervals,.

iVAMS 3.0: Hierarchical-Machine-Learning-Metamodel-Integrated Intelligent Verilog-AMS for Ultra-Fast, Accurate Mixed-Signal Design Optimization Developing Optimal Neural Network Metamodels Based on Prediction Intervals,

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:57:28.051539Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 4fea8c6f-fb74-4529-bd29-d66aab6ebe32 · outbound

This paper cites Neural Network-based Simulation Metamodels for Predicting Probability Dis- tributions,.

iVAMS 3.0: Hierarchical-Machine-Learning-Metamodel-Integrated Intelligent Verilog-AMS for Ultra-Fast, Accurate Mixed-Signal Design Optimization Neural Network-based Simulation Metamodels for Predicting Probability Dis- tributions,

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:57:28.037657Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation b345067d-e4cb-41cf-b498-36063b14750d · outbound

This paper cites Simulation Metamodelling With Neural Networks: An Experimental Investi- gation.

iVAMS 3.0: Hierarchical-Machine-Learning-Metamodel-Integrated Intelligent Verilog-AMS for Ultra-Fast, Accurate Mixed-Signal Design Optimization Simulation Metamodelling With Neural Networks: An Experimental Investi- gation

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:57:28.024048Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation da50c18b-3448-433f-ade9-3f954e2a7716 · outbound

This paper cites Ultra-Fast Variability-Aware Optimization of Mixed- signal Designs Using Bootstrapped Kriging,.

iVAMS 3.0: Hierarchical-Machine-Learning-Metamodel-Integrated Intelligent Verilog-AMS for Ultra-Fast, Accurate Mixed-Signal Design Optimization Ultra-Fast Variability-Aware Optimization of Mixed- signal Designs Using Bootstrapped Kriging,

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:57:28.011009Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 57b6da9e-e559-4727-a931-cb51d5fb58cf · outbound

This paper cites Kriging,.

iVAMS 3.0: Hierarchical-Machine-Learning-Metamodel-Integrated Intelligent Verilog-AMS for Ultra-Fast, Accurate Mixed-Signal Design Optimization Kriging,

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:57:27.998016Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation f0100e3a-8157-4fd6-b566-3d0538fa319a · outbound

This paper cites Particle Swarm Optimization over Non-Polynomial Metamodels for Fast Process Variation Resilient Design of Nano-CMOS PLL,.

iVAMS 3.0: Hierarchical-Machine-Learning-Metamodel-Integrated Intelligent Verilog-AMS for Ultra-Fast, Accurate Mixed-Signal Design Optimization Particle Swarm Optimization over Non-Polynomial Metamodels for Fast Process Variation Resilient Design of Nano-CMOS PLL,

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:57:27.985211Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 4b26c635-662e-4e7e-b64b-63e4fc68c474 · outbound

This paper cites Natick, Massachusetts, United States: The MathWorks Inc., 2012.

iVAMS 3.0: Hierarchical-Machine-Learning-Metamodel-Integrated Intelligent Verilog-AMS for Ultra-Fast, Accurate Mixed-Signal Design Optimization Natick, Massachusetts, United States: The MathWorks Inc., 2012

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:57:27.971997Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation ef1fd54d-c7dd-43c2-9a78-1b0b2fe5ff24 · outbound

This paper cites Analysis of the Publications on the Applications of Particle Swarm Optimisation,.

iVAMS 3.0: Hierarchical-Machine-Learning-Metamodel-Integrated Intelligent Verilog-AMS for Ultra-Fast, Accurate Mixed-Signal Design Optimization Analysis of the Publications on the Applications of Particle Swarm Optimisation,

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:57:27.959030Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 119b6895-6b02-4ab7-8295-d362d4027419 · outbound

This paper cites Transforming Geocentric Cartesian Coordinates to Geodetic Coordinates by Using Differential Search Algorithm,.

iVAMS 3.0: Hierarchical-Machine-Learning-Metamodel-Integrated Intelligent Verilog-AMS for Ultra-Fast, Accurate Mixed-Signal Design Optimization Transforming Geocentric Cartesian Coordinates to Geodetic Coordinates by Using Differential Search Algorithm,

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:57:27.945864Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 1a43b1d7-929a-49db-b664-659efd2d8ac9 · outbound

This paper cites Ant Colony Optimization – Artificial Ants as a Computational Intelli- gence Technique,.

iVAMS 3.0: Hierarchical-Machine-Learning-Metamodel-Integrated Intelligent Verilog-AMS for Ultra-Fast, Accurate Mixed-Signal Design Optimization Ant Colony Optimization – Artificial Ants as a Computational Intelli- gence Technique,

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:57:27.932223Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 0a68e99e-fbc4-4e74-850e-e85e644eca8a · outbound

This paper cites Application of the PSO technique to the Optimization of CMOS Operational Transconductance Amplifiers,.

iVAMS 3.0: Hierarchical-Machine-Learning-Metamodel-Integrated Intelligent Verilog-AMS for Ultra-Fast, Accurate Mixed-Signal Design Optimization Application of the PSO technique to the Optimization of CMOS Operational Transconductance Amplifiers,

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:57:27.917931Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation dd6a9608-0f40-4a26-a30f-eded33bcbd48 · outbound

This paper cites Particle Swarm Optimization over Non-Polynomial Metamodels for Fast Process Variation Resilient Design of Nano-CMOS PLL,.

iVAMS 3.0: Hierarchical-Machine-Learning-Metamodel-Integrated Intelligent Verilog-AMS for Ultra-Fast, Accurate Mixed-Signal Design Optimization Particle Swarm Optimization over Non-Polynomial Metamodels for Fast Process Variation Resilient Design of Nano-CMOS PLL,

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:57:27.904788Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 822d747b-acb3-4e9a-aa53-4559aac1a839 · outbound

This paper cites Statistical Timing Analysis using Levelized Covariance Propagation,.

iVAMS 3.0: Hierarchical-Machine-Learning-Metamodel-Integrated Intelligent Verilog-AMS for Ultra-Fast, Accurate Mixed-Signal Design Optimization Statistical Timing Analysis using Levelized Covariance Propagation,

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:57:27.891498Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation b2a098f7-db19-4168-9499-98597482c2e7 · outbound

This paper cites Modeling and analysis of manufacturing variations,.

iVAMS 3.0: Hierarchical-Machine-Learning-Metamodel-Integrated Intelligent Verilog-AMS for Ultra-Fast, Accurate Mixed-Signal Design Optimization Modeling and analysis of manufacturing variations,

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:57:27.877100Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 4d6afa75-93a9-41b9-9a44-7bbd2c6a82b1 · outbound

This paper cites [Online].

iVAMS 3.0: Hierarchical-Machine-Learning-Metamodel-Integrated Intelligent Verilog-AMS for Ultra-Fast, Accurate Mixed-Signal Design Optimization [Online]

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:57:27.863234Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation e4b8dca2-d4da-468c-978d-675a4afc95e8 · outbound

This paper cites A Surrogate Modeling and Adaptive Sampling Toolbox for Computer Based Design,.

iVAMS 3.0: Hierarchical-Machine-Learning-Metamodel-Integrated Intelligent Verilog-AMS for Ultra-Fast, Accurate Mixed-Signal Design Optimization A Surrogate Modeling and Adaptive Sampling Toolbox for Computer Based Design,

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:57:27.849159Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation aa00817b-5bd9-4b21-aef4-64213667da7d · outbound

This paper cites Accurate Polynomial Metamodeling-Based Ultra-Fast Bee Colony Optimization of a Nano-CMOS Phase-Locked Loop,.

iVAMS 3.0: Hierarchical-Machine-Learning-Metamodel-Integrated Intelligent Verilog-AMS for Ultra-Fast, Accurate Mixed-Signal Design Optimization Accurate Polynomial Metamodeling-Based Ultra-Fast Bee Colony Optimization of a Nano-CMOS Phase-Locked Loop,

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:57:27.835309Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 4e97caff-2474-44d3-bb51-ecacac44da96 · outbound

This paper cites Ordinary Kriging Metamodel-Assisted Ant Colony Algorithm for Fast Analog Design Optimization,.

iVAMS 3.0: Hierarchical-Machine-Learning-Metamodel-Integrated Intelligent Verilog-AMS for Ultra-Fast, Accurate Mixed-Signal Design Optimization Ordinary Kriging Metamodel-Assisted Ant Colony Algorithm for Fast Analog Design Optimization,

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:57:27.821659Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation bb3396f6-888f-418a-9ac5-4a78e15a0a50 · outbound

This paper cites iVAMS 1.0: Polynomial-Metamodel-Integrated Intelligent Verilog-AMS for Fast, Accurate Mixed-Signal Design Optimization.

iVAMS 3.0: Hierarchical-Machine-Learning-Metamodel-Integrated Intelligent Verilog-AMS for Ultra-Fast, Accurate Mixed-Signal Design Optimization iVAMS 1.0: Polynomial-Metamodel-Integrated Intelligent Verilog-AMS for Fast, Accurate Mixed-Signal Design Optimization

Reference 40

Resolution: verified exact; local_arxiv, observed 2026-08-07T11:57:27.808108Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 14d97a3d-d1c5-468b-98f3-bfd494390fdc · outbound

This paper cites iVAMS 2.0: Machine-Learning-Metamodel-Integrated Intelligent Verilog-AMS for Fast and Accurate Mixed-Signal Design Optimization.

iVAMS 3.0: Hierarchical-Machine-Learning-Metamodel-Integrated Intelligent Verilog-AMS for Ultra-Fast, Accurate Mixed-Signal Design Optimization iVAMS 2.0: Machine-Learning-Metamodel-Integrated Intelligent Verilog-AMS for Fast and Accurate Mixed-Signal Design Optimization

Reference 41

Resolution: verified exact; local_arxiv, observed 2026-08-07T11:57:27.788223Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Coverage vector

Reference resolution

Outbound references

Pith citing papers