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Found 8 papers, 1 papers with code
Proof of Efficient Liquidity: A Staking Mechanism for Capital Efficient Liquidity
The Proof of Efficient Liquidity (PoEL) protocol, designed for specialised Proof of Stake (PoS) consensus-based blockchains that incorporate intrinsic DeFi applications, aims to support sustainable liquidity bootstrapping and network security.
Intermediating DFMM Asset (IDA)
The Dynamic Function Market Maker (DFMM) introduced a fully automated framework for operating a multi-asset market, wherein an algorithmic accounting asset was used to connect different liquidity pools and ensure efficient rebalancing of risks, and internal accounting processes.
Dynamic Function Market Maker
We propose an adaptive and automated Dynamic Function Market Maker (DFMM) that addresses challenges in this space.
Explaining Scaling Laws of Neural Network Generalization
In the large width limit, this can be equivalently obtained from the spectrum of certain kernels, and we present evidence that large width and large dataset resolution-limited scaling exponents are related by a duality.
Explaining Neural Scaling Laws
In the large width limit, this can be equivalently obtained from the spectrum of certain kernels, and we present evidence that large width and large dataset resolution-limited scaling exponents are related by a duality.
A Neural Scaling Law from the Dimension of the Data Manifold
We confirm the theory by independently measuring the intrinsic dimension and the scaling exponents in a teacher/student framework, where we can study a variety of $d$ and $\alpha$ by dialing the properties of random teacher networks.
Adaptive Heart Rate Estimation from Face Videos
We propose a novel heart rate (HR) estimation method from facial videos that dynamically adapts the HR pulse extraction algorithm to separately deal with noise from 'rigid' head motion and 'non-rigid' facial expression.
Signal Processing
Guaranteed Safe Reachability-based Trajectory Design for a High-Fidelity Model of an Autonomous Passenger Vehicle
Trajectory planning is challenging for autonomous cars since they operate in unpredictable environments with limited sensor horizons.
Systems and Control
