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Found 11 papers, 1 papers with code
Minimax Optimality of Score-based Diffusion Models: Beyond the Density Lower Bound Assumptions
As a consequence, this yields an $\widetilde{O}\left(n^{-1/2} t^{-\frac{d}{4}}\right)$ upper bound for the total variation error of the distribution of the sample generated by the diffusion model under a mere sub-Gaussian assumption.
$L^1$ Estimation: On the Optimality of Linear Estimators
Consider the problem of estimating a random variable $X$ from noisy observations $Y = X+ Z$, where $Z$ is standard normal, under the $L^1$ fidelity criterion.
NeILF++: Inter-Reflectable Light Fields for Geometry and Material Estimation
We present a novel differentiable rendering framework for joint geometry, material, and lighting estimation from multi-view images.
NeILF: Neural Incident Light Field for Physically-based Material Estimation
We present a differentiable rendering framework for material and lighting estimation from multi-view images and a reconstructed geometry.
On the Value of Interaction and Function Approximation in Imitation Learning
In contrast, when the MDP transition structure is known to the learner such as in the case of simulators, we demonstrate fundamental differences compared to the tabular setting in terms of the performance of an optimal algorithm, Mimic-MD (Rajaraman et al. (2020)) when extended to the function approximation setting.
Efficient Interpolation of Density Estimators
We study the problem of space and time efficient evaluation of a nonparametric estimator that approximates an unknown density.
A Statistical Perspective on Coreset Density Estimation
Coresets have emerged as a powerful tool to summarize data by selecting a small subset of the original observations while retaining most of its information.
Power analysis of knockoff filters for correlated designs
We introduce a simple functional called effective signal deficiency (ESD) of the covariance matrix $\Sigma$ that predicts consistency of various variable selection methods.
Accuracy-Memory Tradeoffs and Phase Transitions in Belief Propagation
The analysis of Belief Propagation and other algorithms for the {\em reconstruction problem} plays a key role in the analysis of community detection in inference on graphs, phylogenetic reconstruction in bioinformatics, and the cavity method in statistical physics.
Communication Complexity of Estimating Correlations
Our results also imply an $\Omega(n)$ lower bound on the information complexity of the Gap-Hamming problem, for which we show a direct information-theoretic proof.
Higher-Order CRF Structural Segmentation of 3D Reconstructed Surfaces
In this paper, we propose a structural segmentation algorithm to partition multi-view stereo reconstructed surfaces of large-scale urban environments into structural segments.
