Customer-obsessed science
Research areas
-
July 10, 20265 min readHydroShear, a new physics-based simulator, teaches robots how to use their sense of touch to perform complex manipulation tasks, in a way that transfers seamlessly to the real world.
-
July 9, 202610 min read
-
-
Featured news
-
MIT Sloan Sports Analytics Conference 20232023Machine learning (ML)-powered football analytics has received considerable interest in recent years, with majority of existing analytic measures centered around offense strategies and performances. In contrast, the defensive side of the game has received relatively less attention and development. At the core of understanding and analyzing any defensive strategy is the coverage scheme, i.e., the rules and
-
ICLR 20232023Humans naturally decompose their environment into entities at the appropriate level of abstraction to act in the world. Allowing machine learning algorithms to derive this decomposition in an unsupervised way has become an important line of research. However, current methods are restricted to simulated data or require additional information in the form of motion or depth in order to successfully discover
-
ICLR 20232023We present HumanEvalX and MBXP, execution-based code completion benchmarks in 10+ programming languages. These datasets are generated by our conversion framework that transpiles prompts and test cases from original datasets (HumanEval and MBPP) to the corresponding data in a target language. Based on these benchmarks, we are able to evaluate code generation models in a multilingual fashion, and in particular
-
IRPS 20232023Investigation of li-ion battery state of health (SOH) degradation and its modeling facilitates determination of device warranty and can provide information about the device battery health. For such studies, batteries undergo life-cycling test with fixed cycling depths and charging currents (C-rates) across cycles, and the gathered degradation data is used for model development. However, in the real world
-
ICASSP 20232023GAN vocoders are currently one of the state-of-the-art methods for building high-quality neural waveform generative models. However, most of their architectures require dozens of billion floating-point operations per second (GFLOPS) to generate speech waveforms in samplewise manner. This makes GAN vocoders still challenging to run on normal CPUs without accelerators or parallel computers. In this work,
Collaborations
View allWhether you're a faculty member or student, there are number of ways you can engage with Amazon.
View all