An interactive architecture for industrial scale prediction: Industry 4.0 adaptation of machine learning. - Ritaban Dutta; Heiko Mueller 001; Daniel Liang (SysCon, 2018)

Applying Vision Based Predictive Modelling for Rapid Characterization of Shape Memory Polymer. - Ritaban Dutta; David Renshaw; Hong Yin; Daniel Liang (BigMine@KDD, 2019)

Machine learning based approach for shape memory polymer behavioural characterization. - Ritaban Dutta; David Renshaw; Cherry Chen; Daniel Liang (Array, 2020)

Characterization of Reversibly-Actuating Shape Memory Alloy Foils Produced By Planar Flow Casting. - Ling Chen; David Renshaw; Michael Kellam; Ritaban Dutta; Daniel Liang (IEEE SENSORS, 2021)

On the Hardness of PAC-learning Stabilizer States with Noise. - Aravind Gollakota; Daniel Liang (Quantum, 2022)

Low-Stabilizer-Complexity Quantum States Are Not Pseudorandom. - Sabee Grewal; Vishnu Iyer; William Kretschmer; Daniel Liang (ITCS, 2023)

An investigation on energy spectral information of computed tomography for machine learning in lesion classification. - Daniel Liang; David Liang; Alice Wei; Licheng Ryan Kuo; Shaojie Chang; Marc Jason Pomeroy; Yongfeng Gao (Computer-Aided Diagnosis, 2023)

Efficient Learning of Quantum States Prepared With Few Non-Clifford Gates. - Sabee Grewal; Vishnu Iyer; William Kretschmer; Daniel Liang (CoRR, 2023)

Clifford Circuits can be Properly PAC Learned if and only if RP=NP. - Daniel Liang (Quantum, 2023)

Low-Cost Generation and Evaluation of Dictionary Example Sentences. - Bill Cai; Clarence Boon Liang Ng; Daniel Liang; Shelvia Hotama (NAACL-HLT, 2024)

Improved Stabilizer Estimation via Bell Difference Sampling. - Sabee Grewal; Vishnu Iyer; William Kretschmer; Daniel Liang (STOC, 2024)

Pseudoentanglement Ain't Cheap. - Sabee Grewal; Vishnu Iyer; William Kretschmer; Daniel Liang (CoRR, 2024)

Agnostic Tomography of Stabilizer Product States. - Sabee Grewal; Vishnu Iyer; William Kretschmer; Daniel Liang (CoRR, 2024)

Tolerant Testing of Stabilizer States with Mixed State Inputs. - Vishnu Iyer; Daniel Liang (CoRR, 2024)

Quantum State and Unitary Learning Implies Circuit Lower Bounds. - Nai-Hui Chia; Daniel Liang; Fang Song (COLT, 2025)

Reinforcement Learning Based Simulated Annealing. - Nathan Qiu; Daniel Liang (AAMAS, 2025)

Hamiltonian Locality Testing via Trotterized Postselection. - John Kallaugher; Daniel Liang (CoRR, 2025)